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THE OCCURRENCE AND DIVERSITY OF INDIGENOUS BRADYRHIZOBIA
THAT NODULATE AND FIX NITROGEN IN SOYBEAN AND PIGEONPEA IN
THREE GHANAIAN SOILS UNDER DIFFERENT LEVELS OF N AND P
FERTILIZERS
By
DANIEL ANSAH FIANKO
(10230001)
THIS THESIS IS SUBMITTED TO THE UNIVERSITY OF GHANA, LEGON, IN
PARTIAL FULFILMENT OF THE REQUIREMENT FOR THE AWARD OF
M.PHIL SOIL SCIENCE DEGREE.
Department of Soil Science
School of Agriculture
College of Basic and Applied Sciences
University of Ghana,
Legon, Accra, Ghana
July, 2014
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DECLARATION
I hereby declare that, this thesis has been written by me and that it is the record of my own
research work. To the best of my knowledge and belief, it has neither in whole nor in part
been presented for another degree elsewhere. Works of other researchers have been cited
and duly referenced. Also all assistances received have been duly acknowledged.
…………………….…………….
……………………..
Daniel Ansah Fianko (Student)
Date
…………………………………
…………………….
Prof. S. K. A. Danso (Principal Supervisor)
Date
…………………………………
………………………
Prof. E. Owusu-Bennoah (Co-supervisor)
Date
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DEDICATION
This thesis is dedicated to the bright memory of Professor S. K. A. Danso, for the advice,
encouragement and immense support both financially and socially that he gave me in
pursuance of my second degree. Unfortunately, he passed on in about a month to the final
submission. May his gentle soul rest in peace.
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ACKNOWLEDGEMENTS
I am most grateful to God Almighty without whose providence and faithful guidance, I
would not have been able to come this far in my academic career.
I also acknowledge, with gratitude, my indebtedness to my supervisors the late Prof. S. K.
A. Danso and Prof. E. Owusu-Bennoah for their time, patience and constructive criticisms
in ensuring a successful write up of my thesis. My special appreciation goes to Dr. (Mrs.)
Stella Asuming-Brempong for taking over the thesis supervision after the sudden demise
of Prof. S.K.A. Danso.
I am extremely grateful to the Council for Scientific and Industrial Research (CSIR) for
providing me with fellowship under the West African Agricultural Productivity
Programme (WAAPP), without which this work would not have been finished
successfully. I am also very grateful to Dr. (Mrs.) R. Entsua Mensah, the Deputy DirectorGeneral, CSIR and all the Coordinators of WAAPP for providing the financial assistance
for this work.
My special thanks go to My Family for their financial and emotional support. For that, I
say I am forever grateful.
My most profound gratitude goes to the management and staff of Ecological laboratory of
the University of Ghana, Legon for granting me access to use the facility.
My heartfelt and sincere appreciation also goes to the teaching and non-teaching staff of
the Soil Science Department especially Mr. Julius Nartenor and Mr. M. S. Elegba,
I acknowledge the assistance given me by Dr. Emmanuel Yaw Boakye and all my
colleague students most especially Ms. Abigail Ama Tettey, Ms. Hellen Agbenyega, Mr.
Daniel Kekeli Tsatsu and Mr. Richard Daffour.
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ABSTRACT
The need to feed the projected world population of 9.7 billion by 2050 has received much
attention and increased food production has been recommended to address the problem.
Soybean and pigeonpea are important global commercial and food legumes that have been
recommended for food security and sustainable agriculture particularly in tropical and subtropical regions where the majority of the world’s resource poor live, and where
agricultural production is constrained by low soil fertility, primarily by soil N and P
deficiencies. It is therefore necessary to enhance the legumes' ability to access more and
more of their N from biological nitrogen fixation, so as to decrease the need for expensive
inorganic N fertilizers especially for these poor farmers. There is, however, limited
information on biological nitrogen fixation and factors that affect this process in Ghana. In
this study, the effects of phosphorus and nitrogen on nodulation, dry weight of nodules
formed and growth of soybean and pigeonpea were determined. Except at excessive rates
of P (160 kg P/ha and 200 kg P/ ha) which decreased nodulation and growth of nodules
formed on pigeonpea in the Haplic Acrisol from the coastal savannah, application of P
increased nodulation and growth of nodules in both pigeonpea and soybean. In contrast to
P, N application to soil inhibited nodulation in the legumes. Application of 80 kg/ha P and
above in combination with an inhibitory rate of N (100 kg N/ ha) revived nodulation and
nodule growth in all cases. The conclusion from this study is that, for a given legume, the
amount of N in a soil's solution that may induce toxicity and subsequently inhibit
nodulation under low P conditions would not be enough to support the growth and
nodulation of that same legume when P is applied to the soil. Such conditions become
favourable for the growth of the legume as well as nodulation in the presence of compatible
bradyrhizobia.
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The effect of the application of P on N acquisition and symbiotic N2 fixation in soybean
plants grown in a coastal savannah Haplic Acrisol was also determined in another study.
Application of P enhanced both % Ndfa and total N fixed. Highest increase in BNF
occurred between the 0 and 40 kg P/ ha. However, highest % Ndfa (54.7 %) and total N 2
fixed (51.5 kg N/ha) occurred when 120 kg P/ ha was applied to the soil. The conclusion
from the study is that nodules were more efficient at fixing N at lower P rates compared to
higher P rates.
In this study, the indigenous populations of bradyrhizobia for cowpea and soybean were
estimated using the most probable number (MPN) plant infection assay. Except for the
Ferric Acrisol which contained very low populations (less than 10 cells/ g soil) of
indigenous soybean Bradyrhizobium, the Haplic Acrisols from the coastal savannah and
semi-deciduous forest both contained satisfactory number of indigenous bradyrhizobia that
were capable of nodulating both Soybean and Cowpea. The diversity of 120 bradyrhizobial
strains isolated from cowpea, soybean and pigeonpea root nodules was investigated using
DAPD and RAPD fingerprinting with primers RPO1 and RPO4, respectively. Based on
the combined RPO1-PCR and RPO4-PCR patterns, a high diversity existed within and
between indigenous bradyrhizobial isolates that nodulated cowpea, pigeonpea and soybean
grown in the soils from the different agro-ecological zones. Phosphorus application had
varying effects on the diversity of isolates from the different soils that nodulated soybean
pigeonpea and cowpea. The conclusion is that, the increased number of nodules formed on
legumes with P application is not always associated with increased diversity of the
compatible bradyrhizobia. Thus bradyrhizobia differ in their soil P tolerance.
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TABLE OF CONTENTS
TITLE
PAGE
DECLARATION ................................................................................................................. i
DEDICATION .................................................................................................................... ii
ACKNOWLEDGEMENTS ............................................................................................... iii
ABSTRACT....................................................................................................................... iv
TABLE OF CONTENTS................................................................................................... vi
LIST OF TABLES ........................................................................................................... xiii
LIST OF FIGURES ......................................................................................................... xiv
CHAPTER ONE ................................................................................................................. 1
1.0
INTRODUCTION .................................................................................................. 1
CHAPTER TWO ................................................................................................................ 7
2.0 LITERATURE REVIEW ............................................................................................. 7
2.1 Introduction ............................................................................................................... 7
2.2 Nitrogen fixation ....................................................................................................... 7
2.2.1 Biological Nitrogen Fixation (BNF) .................................................................. 8
2.3 Legumes .................................................................................................................... 9
2.3.1 Importance of Legumes. .................................................................................. 10
2.3.2 Uses of legumes ............................................................................................... 10
2.3.3 Grain legumes .................................................................................................. 11
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2.4 Rhizobia .................................................................................................................. 15
2.4.1 An overview of rhizobial taxonomy. ............................................................... 16
2.4.2 Rhizobial diversity ........................................................................................... 18
2.4.3 Host Range ....................................................................................................... 21
2.5 The BNF Process .................................................................................................... 21
2.5.1 The root nodule formation ............................................................................... 21
2.5.2 Control of nodule development ....................................................................... 24
2.5.3 Host specificity ................................................................................................ 24
2.6 Importance of BNF ................................................................................................. 26
2.7 Factors Affecting Nodulation and BNF .................................................................. 27
2.7.1Environmental factors that affect BNF ............................................................. 27
2.7.2 Biological Factors ............................................................................................ 35
2.8 Inoculation .............................................................................................................. 36
2.9 Assessment of Nodulation and Nitrogen Fixation. ................................................. 37
CHAPTER THREE .......................................................................................................... 40
3.0 MATERIALS AND METHODS................................................................................ 40
3.1 Soil sampling .......................................................................................................... 40
3.2 Physical Analyses ................................................................................................... 40
3.2.1 Particle Size Analysis ...................................................................................... 41
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3.2.2 Bulk density ..................................................................................................... 42
3.2.3 Field Capacity .................................................................................................. 43
3.3 Chemical analysis ................................................................................................... 43
3.3.1 Soil pH ............................................................................................................. 43
3.3.2 Organic Carbon ................................................................................................ 44
3.3.3 Available Nitrogen ........................................................................................... 45
3.3.4 Total Nitrogen .................................................................................................. 46
3.3.5 Available Phosphorus ...................................................................................... 46
3.3.6 Total Phosphorus ............................................................................................. 47
3.3.7 Exchangeable bases and Cation Exchange Capacity (CEC) Determination ... 48
3.3.8 Exchangeable acidity and Effective Cation Exchange Capacity (ECEC)
Determination ........................................................................................................... 50
3.4 Biological Analysis ................................................................................................. 51
3.4.1 Estimation of the populations of rhizobia in the soils using the Most Probable
Number (MPN) plant infection technique. ............................................................... 51
3.5 Greenhouse Experiment. ......................................................................................... 52
3.5.1 Test crops used................................................................................................. 52
3.5.2 Nitrogen and Phosphorus Response Experiment ............................................. 52
3.5.3 Harvesting ........................................................................................................ 53
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3.5.4 Isolation of N2-fixing bacteria (rhizobia) from root nodules. .......................... 54
3.5.5 Estimation of N2 fixed ..................................................................................... 54
3.6 Statistical Analysis .................................................................................................. 55
3.7 Molecular Characterisation ..................................................................................... 55
3.7.1
DNA Extraction .......................................................................................... 55
3.7.2
PCR Amplification of Genomic DNA using RPO1 and RPO4 Primers .... 56
3.7.3
PCR Amplification of 16S-23S Intergenic Spacer (ITS) and 16S rDNA Gene
57
3.7.4 Cluster Analysis ............................................................................................... 57
3.7.5 Diversity Indices .............................................................................................. 58
CHAPTER FOUR............................................................................................................. 59
4.0 RESULTS ................................................................................................................... 59
4.1 Physical and chemical properties of soils used. ...................................................... 59
4.2 Populations of bradyrhizobia nodulating soybean and cowpea in Adenta, Bekwai and
Nzima series. ................................................................................................................. 61
4.3 Responses of soybean and pigeonpea to nitrogen and phosphorus fertilizer
application in Adenta and Bekwai series. ..................................................................... 62
4.3.1 Phosphorus fertilizer application and nodulation of soybean and pigeonpea. . 62
4.3.2 Effect of phosphorus fertilizer application on dry weight of nodules formed on
soybean and pigeonpea. ............................................................................................ 63
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4.3.3 Nitrogen fertilizer application and nodulation of soybean and pigeonpea ...... 64
4.3.4 Effect of nitrogen fertilizer application on the dry weight of nodules formed on
soybean and pigeonpea. ............................................................................................ 66
4.3.5 Combined application of phosphorus and nitrogen fertilizers on nodulation of
soybean and pigeonpea. ............................................................................................ 67
4.3.6 The combined application of nitrogen and phosphorus fertilizers on the dry
weight of nodules formed on soybean and pigeonpea. ............................................. 68
4.3.7 Effect of phosphorus fertilizer application on shoot dry weight production by
soybean and pigeonpea. ............................................................................................ 70
4.3.8 Effect of nitrogen fertilizer application on shoot dry weight of soybean and
pigeonpea. ................................................................................................................. 71
4.3.9 The effect of the combined application phosphorus and nitrogen fertilizers on
shoot dry weight of soybean and pigeonpea. ............................................................ 72
4.4 Effect of phosphorus application on nodulation and nitrogen fixation in soybean
in Adenta series ......................................................................................................... 74
4.4.1 Effect of phosphorus application on shoot dry weight of soybean grown in the
Adenta and Nzima soils. ........................................................................................... 78
4.5 Genetic diversity of indigenous soybean, pigeonpea and cowpea rhizobial strains in
Adenta, Bekwai and Nzima soils. ................................................................................. 79
4.5.1 Electrophoresed gel images of the PCR amplified products by the different
Primers. ..................................................................................................................... 79
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4.5.2 Clustering on the basis of PCR amplification with RPO1 and RPO4. ............ 83
CHAPTER FIVE ............................................................................................................ 111
5.0 DISCUSSION ........................................................................................................... 111
5.1 Physico-chemical properties of the Adenta, Bekwai and Nzima series. .............. 111
5.2 Populations of indigenous Bradyrhizobia nodulating soybean and cowpea in the
Adenta, Bekwai and Nzima series. ............................................................................. 112
5.3 Effect of P application on nodulation of soybean and pigeonpea grown in the Adenta
and Bekwai series. ...................................................................................................... 113
5.4 Effect of N application on nodulation of soybean and pigeonpea grown in the Adenta
and Bekwai series. ...................................................................................................... 114
5.5 The counteracting effect of P on nodulation inhibition by soil inorganic N by soybean
and pigeonpea grown in the Adenta and Bekwai series. ............................................ 115
5.6 Effect of N and P application on shoot dry weight of soybean and pigeonpea grown
in the Adenta and Bekwai series. ................................................................................ 115
5.7 Effect of phosphorus application on nitrogen fixation by soybean in Adenta series.
.................................................................................................................................... 117
5.8 Diversity of indigenous Bradyrhizobium strains nodulating soybean, pigeonpea and
cowpea in Adenta and Bekwai series as determined by combined RPO1 and RPO4
PCRs. .......................................................................................................................... 118
5.9 Effect of Phosphorus on the diversity of indigenous Bradyrhizobium strains
nodulating soybean, pigeonpea and cowpea in Adenta, Bekwai and Nzima series. .. 119
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CHAPTER SIX ............................................................................................................... 121
6.0 SUMMARY CONCLUSION AND RECOMMENDATIONS ................................ 121
REFERENCES ............................................................................................................... 124
APPENDICES ................................................................................................................ 190
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LIST OF TABLES
TITLE
PAGE
Table 1. Physical and Chemical properties of Adenta, Bekwai and Nzima soils. ............ 60
Table 2. Populations of indigenous soybean and cowpea bradyrhizobia estimated by the
Most Probable Number (MPN) technique. ....................................................................... 61
Table 3. Effect of phosphorus application on nodulation and nitrogen fixation in soybean
grown in Adenta soil. ........................................................................................................ 77
Table 4. Clustering of isolates obtained from cowpea nodules from all the soils at 80 %
similarity ........................................................................................................................... 90
Table 5. Clustering isolates obtained from nodules on pigeonpea grown in the soils at 80
% similarity ....................................................................................................................... 98
Table 6. Clustering isolates obtained from nodules on legumes grown in Adenta soil at 80
% similarity ..................................................................................................................... 103
Table 7. Clustering isolates obtained from nodules on legumes grown in Bekwai soil at 80
% similarity ..................................................................................................................... 106
Table 8. Clustering of isolates obtained from nodules on legumes grown in Nzima soil at
80 % similarity ................................................................................................................ 109
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LIST OF FIGURES
TITLE
PAGE
Fig. 1. Effect of phosphorus fertilizer application on the number of nodules formed on
soybean and pigeonpea grown in the Adenta and Bekwai series ..................................... 63
Fig. 2. Effect of phosphorus fertilizer application on the dry weight (g) of nodules formed
on soybean and pigeonpea. ............................................................................................... 64
Fig. 3. Effect of nitrogen fertilizer application on the number of nodules formed on soybean
and pigeonpea grown in the Adenta and Bekwai series. .................................................. 65
Fig. 4. Effect of nitrogen fertilizer application on dry weight (g) of nodules formed on
soybean and pigeonpea grown in the Adenta and Bekwai series. .................................... 66
Fig. 5. The effect of combined application of phosphorus and nitrogen fertilizers on the
number of nodules formed on soybean and pigeonpea grown in the Adenta and Bekwai
series. ................................................................................................................................ 68
Fig. 6. The combined application of nitrogen and phosphorus fertilizers on dry weight (g)
of nodules formed on soybean and pigeonpea. ................................................................. 69
Fig. 7. Effect of phosphorus fertilizer application on shoot dry weight (g) of soybean and
pigeonpea grown in the Adenta and Bekwai soils. ........................................................... 71
Fig. 8. Effect of nitrogen fertilizer application on shoot dry weight (g) of soybean and
pigeonpea grown in the Adenta and Bekwai series. ......................................................... 72
Fig. 9. Effect of combined application of phosphorus and nitrogen on shoot dry weight (g)
of soybean and pigeonpea. ................................................................................................ 74
Fig. 10. Effect of phosphorus application on shoot dry weight production by soybean
grown in the Adenta and Nzima soils. .............................................................................. 78
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Fig. 11. Sample of PCR amplification of Bradyrhizobium DNA using primer targeting the
16S conserved region. ....................................................................................................... 79
Fig. 12. Sample of PCR amplification of Bradyrhizobium DNA using primer targeting the
23S conserved region. ....................................................................................................... 80
Fig. 13 Sample of PCR amplification of Bradyrhizobium DNA using primer targeting the
16S-23S ITS conserved region. ........................................................................................ 81
Fig. 14. Sample of PCR amplification of Bradyrhizobium DNA using primer RPO1. ... 82
Fig. 15. Sample of PCR amplification of Bradyrhizobium DNA using primer RPO4. .... 83
Fig. 16. Dendogram indicating relationships among cowpea isolates in Adenta soil based
on combined RPO1 and RPO4 PCRs ............................................................................... 84
Fig. 17. Dendogram indicating relationships among cowpea isolates in Bekwai soil based
on combined RPO1 and RPO4 PCRs ............................................................................... 86
Fig. 18. Dendogram indicating relationships among cowpea isolates in Nzima soil based
on combined RPO1 and RPO4 PCRs ............................................................................... 87
Fig. 19. Dendogram indicating relationships among Cowpea isolates in Adenta, Bekwai
and Nzima soil based on combined RPO1 and RPO4 PCRs ............................................ 89
Fig. 20. Dendogram indicating relationships among Pigeonpea isolates in the Adenta soil
based on combined RPO1 and RPO4 PCRs ..................................................................... 92
Fig. 21. Dendogram indicating relationships among Pigeonpea isolates in the Bekwai soil
based on combined RPO1 and RPO4 PCRs ..................................................................... 94
Fig. 22. Dendogram indicating relationships among pigeonpea isolates in the Nzima soil
based on combined RPO1 and RPO4 PCRs ..................................................................... 96
Fig. 23. Dendogram indicating relationships among Pigeonpea isolates in the Adenta,
Bekwai and Nzima soils based on combined RPO1 and RPO4 PCRs ............................. 99
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Fig. 24. Dendogram indicating relationships among soybean isolates in Adenta and Nzima
soils based on combined RPO1 and RPO4 PCRs ........................................................... 101
Fig. 25. Dendogram indicating relationships among isolates from Adenta soil based on
combined RPO1 and RPO4 PCRs .................................................................................. 104
Fig. 26. Dendogram indicating relationships among isolates from Bekwai series based on
combined RPO1 and RPO4 PCRs .................................................................................. 107
Fig. 27. Dendogram indicating relationships among isolates from Nzima series based on
combined RPO1 and RPO4 PCRs .................................................................................. 110
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CHAPTER ONE
1.0 INTRODUCTION
The current 7.1 billion (2013) and projected 9.7 billion by 2050 global population statistics
(PRB, 2013) have resulted in an increased need for food production and distribution (food
security) to support the continuity of the human race beyond 2050 (Nellemann et al., 2009).
Statistics show that, the greater proportion of the population increase will come from the regions
where the resource poor live (PRB, 2013).
The need for combating hunger (promoting food security) through soil fertility replenishment
in sustainable agriculture have received much attention and have yielded good results as can be
seen in the decline of the global hungry people from 1 billion to 842 million in the past two
decades (FAOSTAT, 2013). The decline in the number is obviously not due to increase in death
tolls but as a result of more food being produced and made available to the hungry (Waggoner,
1994; Trewavas, 2001).
The attempts made to increase food production seem paradoxical as efforts in the past two
decades have resulted in a decline in the fertility status of soils under cultivation, especially
those in the tropics and sub-tropics (Koning and Smaling, 2005; Muchena et al., 2005), where
majority of the world’s resource-poor live.
The use of chemical fertilizers (Sanchez et al., 1997) has therefore been recommended as a first
step approach in addressing the problem of soil fertility depletion (Sanchez and Jama, 2002) to
correct primarily for deficiencies in soil nitrogen (N) and phosphorus (P), the two most limiting
plant macronutrients in tropical soils (Bieleski, 1973; Sanchez and Salinas, 1981; Nyemba,
1986; Mengel and Kirkiby, 1987; Smil, 1999; Socolow, 1999; Graham and Vance, 2000; Mamo
et al., 2002).
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The high cost of these fertilizers has, however, deterred poor peasant farmers from using
fertilizers (Sanchez et al., 1997; Vance, 2001). As such, the problem of low soil fertility persists
in tropical and sub-tropical farmers' fields giving low crop yields after cultivation (Kang, 1989;
Mwangi, 1996; Ibeawuchi et al., 2009). In an attempt to increase food production, farmers in
tropical and subtropical regions abandon degraded lands to cultivate new areas (Lobell et. al.,
2009). The soils within the areas that are being relied upon for increased food production in
most cases are marginal and as such, often get depleted of plant nutrients in no time,
consequently, becoming degraded in many cases (Scherr and Hazell, 1994; Scherr and Yadav
1996). The bigger problem is that, the area of degraded lands in the tropical and sub-tropical
regions is always increasing (Hatermink, 2006) warranting an urgent need for restoration.
However, the cost of reclaiming degraded lands and the restoration of soil fertility is very high
(FAOSTAT, 2013) and not all governments are willing to commit resources to that effect.
Whereas phosphorus replenishment strategies are mainly through non-renewable mineralfertilizer supplementation (Sanchez et al., 1997; Ezawa et al., 2002), nitrogen replenishment
may include biologically based strategies such as biologically fixed nitrogen, particularly
through the symbiosis between legumes and rhizobia (Bejiga, 2004) as a supplement to nonrenewable mineral-fertilizer application (Sanchez et al., 1997).
Biological nitrogen fixation (BNF) is a natural process far cheaper than chemical fertilizers and
also environmentally friendly and has therefore been recommended for tropical farmers to
correct for soil N deficiency (Mugwe et al., 2007). Because of their ability to grow in poor soils
or on their lower dependence on the soil’s nitrogen supply, legumes in general and grain
legumes in particular have been suggested in sustainable farming (Jemo et al., 2010). The
symbiosis between these legumes and compatible rhizobia is of greatest agricultural importance
(Anjum et al., 2007; Chianu et al., 2011). In addition, these legumes contribute organic matter
to soils (Valenzuela, 2011).
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Cowpea, soybean and pigeonpea are examples of grain legumes commonly cultivated in Ghana
(Adjei-Nsiah, 2012, Monitor group, 2012). Of these, soybean and pigeonpea are important
commercial and food legumes recommended for food security and sustainable agriculture (
Asgar et al., 2010; Mula and Saxena, 2010; Qiu et al., 2013). Although there is some
information on BNF on legumes such as soybean and pigeonpea in cropping systems in Ghana
(Karbo et al., 1998; Yeboah et al., 2004; Abunyewa and Karbo, 2005; Adjei-Nsiah et al., 2007;
Fening et. al., 2009; Adjei-Nsiah, 2012), there is still room for more studies.
Soybean has been demonstrated to give potential yields of about 4.5-6 MT/ha in Ghana
(Lawson et. al., 2008; MiDA, 2010). However, the current average yield of soybean in Ghana
(0.8 MT/ha) is very low (MiDA, 2010). Although soybean was introduced in Ghana as far back
as 1909 (Snow, 1961; Mercer-Quarshie and Nsowah, 1975), soybean cultivation is mainly
concentrated in the northern sector of the country (Plahar, 2006) despite the vast areas of arable
land (forests and coastal savannahs) available (SRID, 2001) in the southern sector.
Consequently, soybean production in Ghana is very low.
Pigeonpea, another food security legume has a great potential for soils low in both N and P and
an ability to tolerate a wide range of environmental conditions including drought. Pigeonpea is
known to fix large amounts of N and has the ability to release bound sources of P in soil by its
root exudates (Ae et al., 1990). In Ghana, the legume has been found to have a great potential
in the semi-deciduous forest agro-ecological zone, where it increases soil fertility through
nutrient cycling and its ability to grow in the low P soils (Adjei-Nsiah et al., 2007). However,
the potential of pigeonpea as a soil fertility improvement crop through nitrogen fixation
(Peoples et al., 1995) has not been exploited to any appreciable extent and the amount of land
cultivated to pigeonpea in Ghana is very negligible (Adjei-Nsiah, et al., 2007).
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In general little work has been done on the different soils (agro-ecological zones) in Ghana with
regards to; (a) Nutrient requirements of soybean and pigeonpea, (b) Establishing the need for
soybean and pigeonpea inoculation and (c) Isolation and preservation of high quality strains of
rhizobia for inoculant production, and these have also contributed to the low production of these
grain legumes in Ghana.
Phosphorus has been recognized as a key nutrient element in the growth of crops in general and
legumes in particular (Poehlman, 1991; Parvez et al., 2013). Phosphorus serves as a key
constituent of ATP for powering nitrogen fixation and plays significant roles in energy
transformations (Sankar, 1984; Mullins 2001). Gentili and Huss-Danell (2003) have reported
that nodule initiation and growth of legumes have a high P demand and that phosphorus is
necessary for optimizing nitrogen fixation. However, P requirements for maximum nodulation
and nitrogen fixation may differ in different soils (Shu Jie et al., 2007) and for different
legumes. This may be influenced by the different populations of native rhizobia in the different
soils, especially across different agro-ecological zones (Fening, 1999; Klogo, 2006; Boakye,
2013) as well as the difference in soil physical and chemical characteristics across the agroecological zones and also the genetic differences among legume types (Boateng, 2012). In a
recent study, Boateng (2012) reported that, application of phosphorus (TSP) significantly
increased nodulation by cowpea and pigeonpea in a soil from the semi-deciduous rainforest and
also increased nodulation by cowpea, soybean and pigeonpea in a soil from the coastal savannah
agro-ecological zone of Ghana. Soybean did not nodulate at all in the Nzima soil series from
the semi-deciduous rainforest of Ghana.
It is therefore necessary to study the N and P requirements for the successful establishment of
soybean and pigeonpea under low N and P soils and the response of the symbiotic process and
the diversity of the compatible bradyrhizobia to different levels of soil P.
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The research therefore aimed at studying the nodulation and nitrogen fixation of soybean and
pigeonpea under N and P fertilization and the diversity of compatible Bradyrhizobium in
Ghanaian soils under different phosphorus levels. Specifically, the following objectives were
investigated;

To determine the indigenous populations of bradyrhizobia that nodulate soybean, and
cowpea in a Ferric Acrisol from the semi-deciduous forest of Ghana and two Haplic
Acrisols each from the coastal savannah and the semi-deciduous forest zones of Ghana.

To determine the effects of phosphorus and nitrogen levels on nodulation, nodule
growth and growth of soybean and pigeonpea in the Ferric Acrisol and the coastal
savannah Haplic Acrisol.

To determine the effect of Phosphorus on nodulation, total N uptake and symbiotic N2
fixation in soybean plants grown in the Haplic Acrisol from the coastal savannah zone.

To investigate the diversity of indigenous populations of cowpea, pigeonpea and
soybean Bradyrhizobium in the Ferric Acrisol as well as the Haplic Acrisols with or
without phosphorus fertilization.
The following hypotheses were tested;
1. Ho: The population of indigenous soybean and cowpea bradyrhizobia in Ghanaian soils
is low and insufficient to initiate nodulation in these legumes.
HA: The population of indigenous soybean and pigeonpea bradyrhizobia in Ghanaian
soils is high enough to initiate nodulation in these legumes.
2. Ho: The addition of N and P will not affect the nodulation, nodule growth and growth
of soybean and pigeonpea plants.
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HA: The addition of N and P will affect the nodulation, nodule growth and growth of
soybean and pigeonpea plants.
3. Ho: The addition of P will not enhance the nodulation, total N uptake and symbiotic N2
fixation for meeting the total N requirement of soybean grown in the coastal savannah
Haplic Acrisol.
HA: The total N requirements of soybean grown in the coastal savannah Haplic Acrisol
soil could only be met by the symbiosis with P addition.
4. Ho: The genotypic characteristics of the indigenous bradyrhizobia nodulating a
particular legume are not diverse.
HA: There is great diversity among the genotypic characteristics of the indigenous
bradyrhizobia nodulating a particular legume.
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CHAPTER TWO
2.0 LITERATURE REVIEW
2.1 Introduction
This Chapter presents a review of studies conducted on Biological Nitrogen Fixation (BNF) in
legumes in general, and more specifically on soybean and pigeonpea.
2.2 Nitrogen fixation
Nitrogen is a mineral element that plays a very significant role in sustaining life. Till date,
nitrogen still remains the soil nutrient element needed in greatest quantity by crops (Panwar and
Laxmi, 2005; Crosby et al., 2008). Nitrogen occurs in the atmosphere as dinitrogen (N2) gas
constituting about 79 % of all gases, and in a form that is not readily available to vascular plants
(Bundy, 1998; Nolte, 2010). As such there is the need to convert the atmospheric form of
nitrogen into usable forms that are also readily available to these plants for their growth and
development.
Nitrogen fixation is the reduction of the atmospherically stable nitrogen (N 2) to a biologically
useful, combined form (NH3) (Giller and Wilson, 1991). Nitrogen fixation is an important
processes for plant growth and development and the process is second only to photosynthesis
in terms of importance to plants (Hernández, 2002). However, the industrial conversion (also
known as Haber–Bosch process) of the very stable N2 in the atmosphere into usable forms is
costly energy wise (Giller and Wilson, 1991), as it requires 350-550oC of temperature and a
pressure of 150-350 atmospheres. The energy cost alone comprises 70-90 % of the total cost of
producing nitrogen fertilizers (Plewes and Smith 2009). As energy is becoming ever scarcer;
the cost of industrial N will continue to increase posing a great challenge to peasant farmers
who are unable to afford inorganic nitrogenous fertilizers even at today’s prices.
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The equation for the Haber–Bosch reaction (modified from Modak, 2011) is given below.
400𝑜 𝐶
𝑁2(𝑔) + 3𝐻2(𝑔)
>2𝑁𝐻3(𝑔) + ∆𝐻 0 = −90 kJ
200 𝑎𝑡𝑚
Nitrogen fixation also occurs through lightning (Noxon, 1976). However, this is generally
insufficient for extensive crop production as it constitutes only about 10 % of the world's supply
of fixed nitrogen (Zahran, 1999).
Microorganisms through a process termed biological nitrogen fixation (BNF) are able to
convert the atmospherically stable form of nitrogen (N2) into plant usable forms. This microbial
conversion of atmospheric N2 into plant usable forms is highly recommended for sustainable
agriculture (Zahran, 1999). Biological nitrogen fixation is carried out by prokaryotic organisms
that possess the enzyme nitrogenase and use energy in the form of adenosine triphosphate
(ATP).
2.2.1 Biological Nitrogen Fixation (BNF)
Biological nitrogen fixation is a complex biochemical reaction resulting in atmospheric N 2
being enzymatically reduced to NH3 by prokaryotic organisms that possess the enzyme
nitrogenase (Cabello et al., 2012). The reduction (fixation) process can be achieved by
diazotrophic organisms both in the free-living state (free-living fixers) and also in symbiotic
association with plants (Hirsch et al, 2001).
Many cyanobacteria are found in nature as free-living N2 fixing species (Cabello et al., 2009).
Other free living fixers include Klebsiella and Azotobacter. The actinomycetous Frankia
species, cyanobacteria living in association with plants, suitably ferns and rhizobia constitute
the symbiotic fixers which are dominated by the latter (Cabello et al., 2009). Among the
symbiotic fixers, that which is of greatest agricultural importance and as such has received
much attention is the symbiosis between rhizobia and legumes (Cabello et al., 2009). Symbiotic
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nitrogen fixation that occur between legumes and rhizobia involve different hosts and
microsymbionts, respectively (Zahran, 1999; Simon et al., 2007). Biological nitrogen fixation
as used in this thesis refers to the symbiotic nitrogen fixation between legumes and rhizobia.
In order for the nitrogen fixation process to occur, leguminous host plants in the presence of
their compatible rhizobia must enter into a symbiotic or mutually beneficial partnership. The
complex processes and mechanisms involved in the establishment of the partnership results in
the formation of an organ called nodule (Soyano et al., 2013). After a successful partnership
has been established, nitrogen (N2) in the air of soil pores around the nodules is combined with
hydrogen (H2) to form (NH3). The NH3 is further protonated to form NH4+ (Baker and Hall,
1988) which is the actual form of nitrogen assimilated by plants (Schubert, 1995).
The reaction equation below (Cooper and Scherer, 2012) depicts the energy demand of the
biological nitrogen fixation process;
𝑁2 + 8𝐻 + + 8𝑒 − + 16𝐴𝑇𝑃 → 2𝑁𝐻3 + 𝐻2 + 16𝐴𝐷𝑃 + 16𝑃𝑖
2.3 Legumes
Legumes refer to all flowering plants that belong to the family Leguminosae which is the third
largest of flowering plants, comprising slightly under one twelfth of all known flowering plants
(Allen and Allen, 1981; Sprent, 2001). They are found on all continents, except Antarctica
(Sprent, 2001). Many members of the Leguminosa due to their ability to form nitrogen-fixing
symbiosis with rhizobia (Doyle and Luckow, 2003) are of ecological and economic
significance. The leguminosae are classified into three subfamilies (Sprent, 2008), namely,
Caesalpinioideae, Mimosoideae and Papilionoideae which was previously called Fabaceae
(Lewis et al., 2005). The subfamily Papilionoideae includes grain legumes and species of trees,
shrubs, herbs and climbers while the Caesalpinioideae,and the Mimosoideae include species of
trees and shrubs and rarely herbs (de Faria et al., 1989, Batello et al., 2013). Among the
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subfamilies, the Papilionoideae are the most diverse and the most economically important
(Somasegaran and Hoben, 1994; van Berkum and Eardly, 1998). Currently, there are
approximately 750 genera and around 20,000 species in the Leguminosae ranging in habit from
small herbs to huge trees (Elkan, 1992; Lewis et al., 2005). Among the Leguminosae, variability
in nodulation is known to exist (de Faria et al., 1989; Sprent, 2008).
2.3.1 Importance of Legumes.
Legumes, by virtue of their capacity to fix nitrogen, are widely distributed, occupying habitats
ranging throughout the world from rain forests to arid zones, displaying a wide range of
tolerance to acidity, alkalinity, water logging and drought, mineral deficiencies (Rengel, 2002)
among others. As such, they are seen to colonize marginal lands and soils that are impoverished.
In so doing legumes offer several advantages in the rehabilitation of marginalized lands and
degraded soils (Fassil, 1993; Arianoutsou and Thanos, 1996) to promote ecological diversity.
Legumes are known to be environmentally friendly in that, the plants assimilate all the nitrogen
that is fixed by their association with rhizobia with no leaching and ground water pollution
(Reetz, 1989).
2.3.2 Uses of legumes
Throughout history human beings have used legumes in many ways, including as sources of
food, forage, fuel, shelter and traditional medicines (Duke, 1981; Saxena, 1988; Graham and
Vance, 2003; Howieson et al., 2008). This comprises of the not more than 200 species
cultivated. Majority of legumes particularly grain legumes have been incorporated into
agricultural systems to replenish soil N (Adjei-Nsiah et al., 2007).
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2.3.3 Grain legumes
Economically important species of the Leguminosae include grain legumes (pulses and oil
seeds) which belong to the tribe Phaseoleae and pasture legumes. Whilst grain legumes provide
high protein food for humans, both grain and pasture legume species provide high quality feed
for cattle and other small ruminants (Minson et al., 1993; Baker and Dynes, 1999; Howieson,
1999). Additionally, deep-rooted pasture legume species can assist in reducing rising water
tables in areas prone to secondary salinity (Howieson et al., 2000).
Grain legumes together with Arachis (which belongs to Aeschynomeneae) are crops of most
importance in the tropics and account for approximately 20 % of global food production
(Broughton et al., 2003). More than 35 % of the world’s processed vegetable oils and 33 % of
the dietary protein needs of humans come from grain legumes (Broughton et al., 2003).
Grain legumes provide nutritious seeds that are valuable and upon effective nodulation, they
can give promising yields in nitrogen-deficient soils where cereals and other non-leguminous
crops would barely survive (Eaglesham and Ayanaba, 1984).
Among the legumes soybean is the most important globally (Herridge et al., 2008). Below are
short notes on soybean and pigeonpea.
2.3.3.1 Soybean
Soybean also known as Glycine max (L) Merrill is an annual grain legume that is predominantly
found in the tropics (Flaskerud, 2003). The crop is strictly a self-pollinating legume having maturity
dates that range between 90-115 days depending on the variety (Sidibe et al., 1999). The leading
soybean producers in the world are USA, Brazil, Argentina and China (Song et al., 2006).
Soybean seeds are composed of roughly 22 % lipids, about 30.16 g of carbohydrates, 7.33 g
sugar, 2.88 g saturated fat and many other nutrients (Song et al., 1999).
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2.3.3.1.1 Uses
Oil (including lecithin) and protein (meal or flour) are two major components of soybean seeds
that are used as raw materials for manufacturing printers’ ink, cosmetics, plastics, glue, soap,
shampoo and many more (Endres, 2001). Other products made from soybean include detergents
and gasoline (mainly in the USA) (Adu-Dapaa et al., 2004; Kamara, 2013). Soybean is also
used industrially for making paints, water–proofings for textiles, and a sizing for paper
(Shurtleff and Aoyagi, 2009) and also for the production of margarine, cheese, and others
(Shurtleff and Aoyagi, 2012).
Soybean has a great potential for solving the protein energy malnutrition problems in West
Africa and the World at large (Asgar et al., 2010). Soy milk and soy flour/powder are products
of unfermented soybean (Mariansky and Mariansky, 2011; Viska et al., 2013). Fermented
soybean foods include soy sauce, fermented bean paste, natto and tempeh, among others
(Mariansky and Mariansky, 2011; Viska et al., 2013).
2.3.3.1.2 Importance
Fixed atmospheric nitrogen in soybean improves soil fertility and subsequently enhances
sustainable crop production especially when in rotation with cereals (Mohammad et al., 2008).
Soybean plants provide good soil cover that reduces soil erosion and suppresses weed growth
(Moncada and Sheafer, 2010). It also breaks pest and disease cycles when grown in rotation
with cereals (Aikins et al., 2011; Kamara, 2013). Soybean is known to cause suicidal
germination of Striga seeds and hence reduce the population of Striga for a successful cereal
production in the subsequent year of a rotational cropping (Adu-Dapaa et al., 2004; Kamara,
2013).
Soybean contains significant amounts of essential amino acids which are of great importance
to both human and animal health (Symolon et al., 2004). Isoflavones from soybeans have
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recently been suggested to reduce the risk of cancer and serum cholesterol (Guha et al., 2009;
Shu et al., 2009) while phytoestrogen from soybean and soy foods have been suggested as a
possible alternatives to hormone replacement therapy for post-menopausal women (Graham
and Vance, 2003).
Soybean has a great potential towards developing some key sectors of a nation’s economy such
as Health, Agriculture and Industry (Plahar, 2006; World Initiative for Soy in Human Health,
2006). The economic benefits derived from soybean production have been documented
extensively by Egbe (2010).
2.3.3.1.3 Soybean Cultivation in Ghana
The earliest known cultivation of the soybean crop in Africa was in Algeriain 1896, (Shurtleff
and Aoyagi, 2009). Soybean was first grown in Ghana in 1909 (Mercer-Quarshie and Nsowah,
1975; Snow, 1961). However, there was no serious attempt to establish the production of the
crop in Ghana until the early 1970s (Mercer-Quarshie and Nsowah, 1975).
2.3.3.2 Pigeonpea
Pigeonpea also known as Cajanus cajan (L.) Millsp is a tropical grain legume that is grown in
a wide range of cropping systems and environments (climates and soils) (Nene and Sheila,
1990), notable exceptions being those areas that are excessively wet or that experience frost
(Troedson et al., 1990). Although pigeonpea is a woody perennial, the legume is grown mainly
as an annual (Giller, 2001). Depending on the variety, pigeonpea can take from 90-260 days to
produce seed (Van de Maesen, 1985; Ali, 1990). The crop although can tolerate a wide pH (4.58.4) range, grows best at soil pH 5.0-7.0. It can withstand a temperature of 350C or more
(Valenzuela and Smith, 2002). The crop was probably domesticated in India. However, just
before 2000 BC, the legume spread to Africa, a second centre of diversity (Van de Maesen,
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1985). A wild species of pigeonpea (Cajanus kerstingii) still exists in West Africa (Giller,
2001). The legume was later carried from Africa to the West Indies (Giller, 2001).
2.3.3.2.1 Uses
Pigeonpea is a protein-rich pulse crop that has growing demand in Asia, especially in India
because it can provide high quality protein in the diet of humans (Lee et al., 2006). The plant
has got immense medicinal value and is also used as fodder for cattle and other small ruminants
(Singh and Diwakar 1993; van der Maesen, 2006; World Initiative for Soy in Human Health,
2006).
2.3.3.2.2 Importance
As a multipurpose leguminous crop, pigeonpea can provide food, fuel wood and fodder for
small-scale farmers in subsistence agriculture (Tabo et al., 1995; Egbe, 2005). The legume is
deep-rooted and also drought tolerant and as such adds organic matter to the soil (Egbe, 2005).
Pigeonpea in addition can fix up to 235 kg N/ha (Peoples et al., 1995) thus producing more N
per unit area from plant biomass than many other legumes.
Pigeonpea is nutritionally well balanced and is an excellent source of proteins (20–30 %)
(Snapp et al., 2003). In addition to proteins, pigeonpea provides carbohydrates and high levels
of vitamins A and C.
Farmers who grow pigeonpea can derive benefit in the form of income which is usually by
computing the monetary advantage (Rafey and Prasad, 1992) or by estimating the net returns
(Ramakrishna et al., 2005; Guedes and Araujo, 2010). The importance of intercropping
pigeonpea with cereals are available (Egbe, 2005; Egbe and Adeyemo, 2006; Egbe and BarAnyam, 2011).
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2.3.3.2.3 Pigeonpea Cultivation in Ghana
Pigeonpea is mostly cultivated in India and eastern Africa. In Ghana, the crop is mainly grown
on pastures (Adjei-Nsiah et al, 2007). Being the major pigeonpea producing country, India
accounts for over 93 % of the global pigeonpea production (Rani, 2011). Other researchers have
reported Nigeria (Aiyeloja and Bello, 2006), Niger, Mali, Benin (Versteeg and Koudokpon,
1993), Ethiopia, Zimbabwe (Kamanga and Shamudzarira, 2001), Zambia (Boehringer and
Caldwell, 1989), Botswana (Amarteifio et al., 2002), and South Africa (Swart et al., 2000) to
be other pigeonpea producing countries in Africa.
Pigeonpea derives between 36.10-114.04 kg N/ha from fixation when intercropped with maize
and 35.94-164.82 kg N/ha under intercropping with sorghum (Egbe, 2007). However, yields in
Nigeria have been reported to be as low as 0.5-1.0 t/ha under traditional cropping systems (Egbe
and Idoko, 2012). The story is the same for Ghana, where yield of pigeonpea ranges from 1291872 kg/ ha with an average of 946 kg/ ha. This is very low compared to an average yield of
2600 kg/ ha by the same pigeonpea lines grown in India (Marfo et al., 1997). The low yield
could be as a result of production being concentrated in the semi-deciduous forest zones where
other legumes are preferred to pigeonpea in intercropping. Adjei-Nsiah (2012) reported that
pigeonpea seed consumption is low and is caused by low knowledge on pigeonpea meals
making farmers place a much less priority on the legume for intercropping.
2.4 Rhizobia
Rhizobium in Latin means ‘root living’ which is why they are also referred to as root nodule
bacteria (RNB). Rhizobia are facultative microsymbionts (Provorov, 1998) that can infect roots
of most legumes (Hirsch et al., 2001; Matiru and Dakora, 2004) and transform atmospheric N2
into forms usable by plants (Phillips, 1999; Bala and Giller, 2001; Sessitsch et al., 2002).
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Rhizobia are Gram negative, motile, rods that are pleomorphic under adverse growth conditions
(Jordan, 1984). They usually accumulate granules of poly-β-hydroxybutyrate when carbon is in
excess and are aerobic, possessing a respiratory type of metabolism with oxygen as the terminal
electron acceptor (Jordan, 1984).
2.4.1 An overview of rhizobial taxonomy.
Early classification of rhizobia was based on the cross inoculation group concept, which
grouped rhizobia on the basis of their ability to infect and fix nitrogen with a discrete group of
legumes (Jensen, 1958). The concept of cross inoculation was disproved by Zakhir and Lajudie
(2001).
Originally, all the root nodule bacteria (RNB) were placed together in the family Rhizobiaceae
(Jordan, 1984) which consisted of the genera Rhizobium (Vincent, 1974), Sinorhizobium (Chen
et al., 1988), Mesorhizobium (Jarvis et al., 1997), Allorhizobium (de Lajudie et al., 1998),
Azorhizobium (Dreyfus et al., 1988) and the slow-growing Bradyrhizobium (Jordan, 1982).
Extensive study and classification of rhizobia (Broughton, 2003) has brought about changes in
the taxonomy. This has led to revisions and additions to the taxonomy of rhizobia (Jordan,
1984). The revisions have revealed progress in rhizobial taxonomy and systematics notably in
the last decade which is mainly due to the characterization of new isolates together with the
general use of 16S rRNA sequencing and polyphasic taxonomic approaches (van Berkum and
Eardly, 1998; Zakhir and Lajudie, 2001).
Currently, there are 44 species of RNB that have been accepted and they are distributed in 12
genera in the class α-Proteobacteria (Sawada et al., 2003) and the β-Proteobacteria (Chen et
al., 2001).
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The α-Proteobacteria class consists of five families: Rhizobiaceae (including the genera
Allorhizobium/shinella, Rhizobium and Sinorhizobium/Ensifer), Phyllobacteriaceae (including
the genus Mesorhizobium), Bradyrhizobiaceae (including the genus Bradyrhizobium),
Hyphomicrobiaceae
(including
the
genera
Azorhizobium
and
Devosia)
and
Methylobacteriaceae (including Methylobacterium) as defined by their 16S rDNA sequence
analysis (Garrity et al., 2003; Sawada et al., 2003; Rengel, 2002). Those in the β-Proteobacteria
class are contained in two familes: Burkholderiaceae (including the genera Burkholderia and
Wautersia) (Garrity et al., 2003; Sawada et al., 2003) and Ralstoniaceae (including the genus
Ralstonia) (Chen et al., 2001; Moulin et al., 2001).
Soybean is nodulated by Bradyrhizobium japonicum, Bradyrhizobium elkanii (Kuykendall et
al., 1993), Bradyrhizobium liaoningense (Xu et al., 1995) and Sinorhizobium fredii (Chen et
al., 1988 Young et al., 2001).
Pigeonpea is nodulated by Rhizobium leguminosarum bv viceae and Bradyrhizobium spp.
(Nautiyal et al., 1988; Singh et al., 1997). Below are notes on the main rhizobia genera from
which soybean and pigeonpea are nodulated.
2.4.1.1 The genus Rhizobium
Rhizobium refers to the fast growing, acid-producing strains of rhizobia. There are three species
within this genus. They are Rhizobium phaseoli, Rhizobium trifolii and Rhizobium
leguminosarum. Rhizobium leguminosarum consists of three biovars named to distinguish their
plant affinities: biovar viciae as it nodulates Vicia spp.; biovar trifolii as it nodulates Trifolium
spp. (clover) and biovar phaseoli as it nodulates Phaseolus vulgaris (common bean) (Jordan,
1984). The host ranges of the three biovars are quite distinct and seem to be mutually exclusive.
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2.4.1.2 The genus Bradyrhizobium
The genus Bradyrhizobium refers to bacteria that are extremely heterogeneous and different from
other legume symbionts by their slow growth and production of alkaline reactions in growing
media (Jordan, 1984). The species of this genus include Bradyrhizobium japonicum,
Bradyrhizobium elkanii, Bradyrhizobium liaoningense and Bradyrhizobium spp.
2.4.1.3 The genus Ensifer/Sinorhizobium
Until recent times, all fast-growing rhizobia were put under the genus Rhizobium including
Rhizobium fredii a fast-growing soybean Rhizobium. Continues research later on lead to the
renaming of Rhizobium fredii as Sinorhizobium fredii and a second species, Sinorhizobium
xinjiangense was proposed Chen et al. (1988). The genus Sinorhizobium is now widely
accepted and currently has 11 valid species. There is genetic evidence to support the separation
of S. xinjiangense and S. fredii (Peng et al., 2002). Recent comparisons using the 16S rDNA
has revealed that Ensifer adhaerens is a phylogenetic member of the Sinorhizobium lineage
(Balkwill, 2005). In a 16S rDNA dendrogram, Ensifer and Sinorhizobium form a single group
which belongs alpha-Proteobacteria and the two may therefore be regarded as a single genus.
Efforts to choose the appropriate name Sinorhizobium adhaerens or Ensifer adhaerens
(Willems et al., 2003, Young, 2003) for the genus are still ongoing. As of now Ensifer
adhaerens is preferred and remains the correct name.
2.4.2 Rhizobial diversity
The variation in the DNA sequences between strain types in a rhizobial population is called
genetic diversity (McInnes, 2002). The strains of RNB inhabiting a particular soil may be
diverse in symbiotic as well as phenotypic and genetic characters (Pinto et al., 1974). Cropping
history, the degree of disturbance of an environment and the range of legume species of an area
can influence the diversity of rhizobial strains in that area (Brockwell et al., 1995) as well as
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strain population in the area. In measuring diversity, it is important to note that measuring the
diversity of RNB using a trap host only resembles the diversity of RNB able to nodulate that
particular trap host and not the total diversity of RNB resident in the soil. Many studies have
assessed the diversity of RNB strains nodulating a particular legume species or the diversity of
RNB that exist in a particular soil (Laguerre et al., 1996; Lafay and Burdon, 1998; Wang et al.,
1999; Zhang et al., 2000).
Many attempts have been made to determine the actual composition and characteristics of
indigenous rhizobia using strains isolated from different cultivated legumes (Laguerre et al.,
1996; Carelli et al., 2000). There increased attention in the assessment of diversity within
rhizobial natural populations in various regions of the world (Chen et al., 2000; Zhang et al.,
2000) in the last few years gives an indication that the subject has not been fully exhausted.
The development and availability of several sensitive and accurate PCR-based genotyping
methods (Jensen et al., 1993; Jude et al., 1993; Selenska-Pobell et al., 1995) have helped in the
differentiation of closely related bacterial strains even among natural field populations. There
has also been detection of higher rhizobial diversities compared to previous times (Vinuesa et
al., 1998; Doignon-Bourcier et al., 2000; Tan et al., 2001). It is important to note, however,
that the discriminatory power of individual strain typing methods varies and this can give rise
to different diversity assessments for the same field site tested (Schwinghamer and Dudman,
1980; Barnet, 1991; Bottomley, 1992) even for a particular legume species.
At present there is a substantial array of techniques used for detecting and describing rhizobial
diversity and they are discussed in the next section.
2.4.2.1 Methods used to investigate rhizobial diversity
Phenotypic and physiological characters such as host range, comparative growth in culture,
serological relatedness, bacteriocin production, intrinsic antibiotic resistance and bacteriophage
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resistance (Schwinghamer and Dudman, 1980) were previously used to determine rhizobial
diversities. The recent molecular era has enabled the inclusion of more prominent methods such
as substrate utilization, protein profiling, Multilocus Enzyme Electrophoresis (MLEE) and
Fatty Acid Methyl Ester (FAME) analysis in assessing rhizobial diversity (Graham et al., 1995;
Van Rossum et al., 1995). The phenotypic and physiological methods used in times past had
some limitations, particularly, low discriminatory power compared to molecular methods
(Jenkins and Bottomley 1985; Barnet, 1991; Bottomley, 1992) and also an often poor
correlation between strain groupings (Kleczkowsky and Thornton, 1994; Roughley et al., 1992;
van Rossum et al., 1995) which were due to the instability of strain characters over time
(Lindström et al., 1990).
In recent times, there are large numbers of genotypic (molecular based) methods used for
rhizobial diversity studies and the most common methods comprise:
1. Plasmid profiling (Broughton et al., 1987; Young and Wexler, 1988; Laguerre et al.,
1992; Louvrier et al., 1996; Wernegreen et al., 1997)
2. Restriction Fragment Length Polymorphism (RFLP) (Schofield et al., 1987; Young
and Wexler, 1988; Laguerre et al., 1993; Bromfield et al., 1995; Kishinevsky et al.,
1996; Lafay and Burdon, 1998; Vinuesa et al., 1998; Odee et al.. 2002)
3. Polymerase Chain Reaction based techniques (PCR) (de Bruijn, 1992; Richardson et
al., 1995; Louvrier et al., 1996; Laguerre et al., 1997; Gao et al., 2001)
Genotypic methods generally have high discriminatory power and the majority of these
methods are rapid compared to most phenotypic methods (Handley et al., 1998). However, it is
important to note some of their limitations. Most of the genotypic methods used in diversity
studies, especially the PCR based techniques (BOX PCR, ERIC PCR, Rep PCR and RPO1
PCR) are reported to be of low reproducibility. Their success is mostly dependent on the DNA
extraction protocol, colony age, source of reagents, concentration and purity, and thermal
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cycling conditions (Welsh and McClelland, 1990; Coutinho et al., 1993; Kay et al., 1994;
Richardson et al., 1995; Laguerre et al., 1996; Vachot et al., 1999). These disadvantages can
however be overcome by rigorously standardising the protocols, using many repeats, replicates
and including appropriate controls.
2.4.3 Host Range
A proper definition of host range is to consider the diversity of the symbiotic genes rather than
the diversity of the species that carry these genes (Laguerre et al., 2001). The success of clearly
defining the host range of newly identified strains was due to the recent development molecular
techniques. The phylogenetic classification of genes is now used for the description of new
rhizobia as previously proposed for the 16S rRNA gene sequences (Graham et al., 1991).
2.5 The BNF Process
2.5.1 The root nodule formation
The process of nodulation (root nodule formation) involves the transfer of signals between a
legume host plant and compatible rhizobia. The process is commenced by the release of organic
compounds from the roots of host legumes (Gualtieri and Bisseling, 2000) into the rhizosphere
most of which supports the growth of rhizosphere microorganisms (Barran and Bromfield,
1997; Perret et al., 2000). The rhizosphere environment must be appropriate prior to the
successful exchange of the signal molecules that precede infection (Leibovitch et al., 2001;
Zhang et al., 2002). The released compounds (exudates) consist mainly of carbohydrates,
organic acids, vitamins, amino acids and flavonoids (2-phenyl-1, 4-benzopyrone derivatives)
(Rélić et al., 1994; Broughton et al., 2000; Perret et al., 2000).
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In nodulating plants, flavonoids specifically trigger the expression of the rhizobial genes
required for nodulation (nod). The importance of flavonoids is seen in the complete inhibition
of nodule initiation whenever these flavonoids are absent (Perret et al., 2000).
The nod genes are responsible for the synthesis of the nodulation factors, which are involved in
the establishment of the symbiotic relationship with the legume host (Perret et al., 2000). The
types and functions of these 'nod' genes have been documented extensively (Triplett and
Sadowsky, 1992; Van Rhijn et al., 1993; Downie, 1998; Hirsch et al., 2000; Perret et al., 2000;
Zhang et al., 2000). The nod genes are organized in several operons, located on the chromosome
(Kaneko et al., 2000) or on a mobile symbiosis island which is integrated into the chromosome
(Sullivan et al., 2002) or on large symbiotic (sym) plasmids (Hynes and MacGregor 1990; Brom
et al., 1992; Triplett and Sadowsky, 1992; Barnett et al., 2001; Finan et al., 2001)
The rhizobial nod genes often produce and secrete nodulation (Nod) factors as return signals in
response to the flavonoids secretion from host plants. Each rhizobial strain produces a
characteristic spectrum of Nod factors that is generally unique for a given isolate (Downie,
1998; Schultze and Kondorosi, 1998). Nod factors are the signals required for the entry of
rhizobia into the leguminous plants acting like ‘keys’ for the invading rhizobia to the legumes
root hair ‘doors’ (Broughton et al., 2000; Gualtieri and Bisseling et al., 2000; Parniske and
Downie, 2003). Additional signals, or ‘keys’, which normally proceed the entry of rhizobia are
necessary for later steps of the infection process (Perret et al., 2000).
The root hairs of the host legumes are induced to branch upon contact with the Nod-factors.
The branched roots then after deform and curl thereby preventing further root hair cell growth.
Bacterial cells are trapped in pockets of the host cell wall at the curled regions. The root hair
cell walls undergo hydrolysis at certain sites where bacteria entry of the roots of host legumes
occurs. The entry process is described as ‘penetration through an invagination of the plasma
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membrane’. The plant host reacts to bacterial entry by depositing new cell wall material around
the lesion. This is usually in the form of an inwardly growing tube that later becomes what is
called infection thread (Vanderleyden and Van Rhijn, 1995; Hirsch and LaRue, 1997; Gage and
Margolin, 2000; Gualtieri and Bisseling, 2000). The infection thread is the medium through
which rhizobia penetrate root tissues (Sprent, 1989, 2001; Brewin, 1991; Gage et al., 1996;
Hadri et al., 1998; Gage, 2004; Oldroyd and Downie, 2004; Maunoury et al., 2008). The
rhizobial infection of the roots of some legumes is through a wound or crack (Gonzalez-Sama
et al. 2004). At the time a Rhizobium penetrates the root tissue, there is cell division in the outer
or inner root cortex which results in the production of a nodule primordium. Bacteria are
released from the infection threads into the host cytoplasm within the growing nodule
primordium where they are differentiated into bacteroids and the nitrogen-fixing nodule
develops (Roth and Stacy, 1989; Gualtieri and Bisseling, 2000). As the nodule develops in the
presence all other requirements, there is fixation of atmospheric N2 in the air surrounding the
nodule (Long and Ehrhardt, 1989). The inside colour of a nodule with active nitrogen fixation
is usually red or pink. The red colour is due to leghaemoglobin, an iron-containing pigment
associated with active nitrogen fixation (Bergersen, 1982). The number of nodules and the rate
of nitrogen fixation will increase with time after emergence and normally reaches a maximum
just before the legume blooms (Imsande, 1988).
Ineffective rhizobia often produce nodules, but these nodules are small and white, grey or green
on the inside (Starker et al., 2006). Where legumes are ineffectively nodulated, the plants show
symptoms of nitrogen deficiency, i.e. progressive yellowing of the leaves and generally poor
growth is observed (Meyer et al., 2007).
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2.5.2 Control of nodule development
Host plants possess the genetic information for symbiotic infection and nodulation
(Vanderleyden and Van Rhijn, 1995). This means what the bacteria does is to switch these host
plant genes on. The positive as well as negative (expression of the nod genes) actions of these
plant genetic factors (Suzaki et al., 2013), are what control the development of nodule. The
regulation of the symbiotic process in most cases is influenced by external factors such as
nitrogen in the soils solution (Caetano-Anollés, 1997). The plant host limits the number of
nodules and this regulation might be integrated in the mechanisms that control lateral root
development (Stougaard, 2000).
2.5.3 Host specificity
The amounts of Nod factors released by rhizobia are important in determining the host range
(Perret et al., 2000) and specificity. During the formation of symbiotic associations, there
appears to be communication between the symbiotic partners, leading to their recognition of
each other (Schultze and Kondorosi, 1998). Specificity is not only confined to nodulation but
also extends to the ability to form effective, nitrogen-fixing nodules. Only certain combinations
of host plants and effective rhizobia are compatible with each other to form a nitrogen-fixing
symbiosis (van Rhijn et al., 1998). Various 'nod' gene inducers, Nod factors and
polysaccharides are all involved in determining host specificity (van Rhijn et al., 1998). Certain
rhizobial isolates are capable of forming effective nodules on some host legumes (Nod+, Fix+)
whilst forming ineffective nodules on others (Nod+, Fix -) (Valverde et al., 2005). Specificity
among compatible partners minimizes the chance of pathogen infection and the formation of
ineffective associations (Perret et al., 2000).
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2.5.3.1 Molecular basis of host specificity
The specificity in the symbiotic interaction between legumes and rhizobia is controlled at many
levels. The type of NodD protein present in the RNB, the type of the flavonoid produced by the
legume host, the type of Nod-box in the promoter region of nodulation genes and the type(s) of
Nod-factor produced by the RNB are the four important levels in that order at which the
symbiosis establishment is controlled (Sadowsky and Graham, 1998).
That different species produce different NodD proteins which respond to different types of plant
flavonoids (Downie, 1994) buttresses this point. NodD1 of the broad host range Rhizobium sp.
strain NGR234 recognises a wide range of flavonoids and transfer of the nodD1 of strain
NGR234 to other strains of restricted host range has been shown to extend the host range
(Bender et al., 1988). Thus, the initial level in symbiotic specificity is controlled by nodD.
When conditions in the soil results in the release of flavonoids from plant roots, the bacterial
NodD or SyrM (Barnett and Long, 1990; Schlaman et al., 1992) proteins activate the
transcription of other nod genes (Roche et al., 1996; Downie, 1998). The activation of the
transcription of other nod genes regulates the initial infection process. NodD and SyrM proteins
act as both plant signal sensors and transcriptional activators (Perret et al., 2000) triggering the
transcription of the nodABC operon in RNB by binding to the Nod-box in the promoter region
of this operon. Rhizobium sp. strain NGR234, which can nodulate a broad range of legumes,
contains 19 different homologous sequences for Nod-box, thereby providing many possibilities
for fine-tuning nod gene expression (Perret et al., 2000).
The specificity between legume hosts and RNB can range from the highly specific, i.e. where
only a single species of RNB nodulate a given legume host (Nour et al., 1994, 1995; MartínezRomero, 2003), to being very promiscuous (Michiels et al., 1998). The specificity is often is
governed by a single recessive gene, sym-2 (Holland, 1975; Lie, 1984).
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Symbiotic promiscuities usually exists in two forms.
1. The promiscuity of RNB (broad host-range RNB): Where a single RNB strain enter
into symbiosis with a range of different host plants (Perret et al., 2000).
2. The promiscuity of the host plant: A single legume may be nodulated by a range of
RNB belonging to different species (Bromfield and Barran, 1990; Laguerre et al.,
1993; Ezura et al., 2000; Aguilar et al., 2001; Howieson and Ballard, 2004).
Promiscuity in RNB his a valuable trait for elite inoculants selected for commercial use
(Howieson et al., 2000). Such strains must form highly effective symbiosis on a wide range of
host legume species (Howieson, 1999; Howieson et al., 2000). Ineffective nodulation by
promiscuous RNB that are indigenous or resident in agricultural soils reduces the benefits of
legume inoculation to agriculture (Demezas and Bottomley, 1984; Barran and Bromfield 1997;
Ballard and Charman, 2000; Denton et al., 2002).
Promiscuous legume species may face reduced productivity due to nodulation by a range of
ineffective or less effective RNB (Trinick and Hadobas, 1989; Hungria and Vargas, 2000). As
such commercial legume species with the ability to form effective nodules with many different
soil rhizobia (Abaidoo et al., 2000; Sessitsch et al., 2002; Howieson and Ballard, 2004) should
be considered.
2.6 Importance of BNF
Biological nitrogen fixation is undoubtedly of greatest agricultural importance as it occurrs in
all known ecosystems. On a global scale, nitrogen derived from biological nitrogen fixation
may reach 175 million metric tons per year (Graham et al., 1994) of which approximately 90
million tonnes come from agricultural areas. Undeveloped land and forests (Bezdicek and
Kennedy, 1988) contribute approximately 50 million tonnes of N from BNF.
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The importance of biological nitrogen fixation is seen in the nitrogen nutrition of leguminous
plants and their associated crops in natural and agricultural systems. Most grain legumes can
obtain between 50 to 80 % of their total nitrogen requirements through biological nitrogen
fixation, although some, like faba bean can fix up to 90 % (Herridge et al., 2008; Salvagiotti et
al., 2008).
The input of nitrogen through biological nitrogen fixation allows for increased soil fertility,
which helps to maintain soil nitrogen reserves (Graham and Vance, 2000) without having much
adverse effect on the environment compared to chemical N fertilisers.
2.7 Factors Affecting Nodulation and BNF
The establishment of an effective rhizobia-legume symbiosis requires colonization and survival
of rhizobia in the soil as saprophytes competing with other indigenous microbes and genetic
compatibility with the host legume under a favourable environment to allow maximum
nodulation and N2 fixation (Bordeleau and Prevost, 1994).
2.7.1Environmental factors that affect BNF
Typical environmental stresses that affect legume nodulation and the subsequent symbiotic
nitrogen fixation include photosynthetic deprivation, soil moisture, salinity, soil nitrate and
phosphate levels, soil acidity and alkalinity and temperature (Walsh, 1995).
2.7.1.1 Soil Moisture content
The rhizobial population density in a soil (Tate, 1995), rhizobial migration, nodule number and
size (Williams and De Mallorea, 1984) is negatively affected by soil moisture. The effect is
more pronounce on N2-fixation as nodule initiation, growth and activity are more sensitive to
water stress (Bordeleau and Prevost, 1994) than are root and shoot metabolism (Albrecht et al.,
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1994). In dry soil, infection of root hairs is restricted because roots become short, stubby and
inadequate for rhizobial infection (Lie, 1981).
Excess soil water (a case of saturated soils) is also detrimental to N2-fixation because it lowers
oxygen diffusion for nodule functions and may lead to a build-up of CO2 (which inhibits nodule
formation) and ethylene (which restricts nodulation even at low concentrations) (Eaglesham
and Ayanaba, 1984),
When the surface of soils are dry at the time of planting, most of the bacteria on inoculated
seeds are killed thereby decreasing the nodulation of the plant. A common observation with
many strains of all species of Rhizobium, is the 99 % reduction in the viable population upon a
single exposure of the soil to drying. Several cycles of soil wetting followed by drying, a
common phenomenon of nature, reduces the population still further (Alexander, 1985).
Although more than 99 % of the cells of other strains die under identical circumstances
(Osa-Aftana and Alexander 1982), it appears, that means can be devised to obtain cultur es
not seriously affected by the drying of soil.
2.7.1.2 Temperature
Biological nitrogen fixation is affected under high soil temperatures (Michiel et al., 1994) since
rhizobial survival in very warm soil is so low. Soil temperatures above 20°C at seeding time
will kill many rhizobia and greatly decrease nodulation. In some cases high temperatures may
cause the symbiotic process to cease completely (Bordeleau and Prevost, 1994). Low
temperature also delays root hair infection and decreases nodulation as well as nitrogenase
activity (Waughman, 1977). Extreme temperatures affect root hair infection, bacteroid
differentiation, nodule structure and functioning (Roughley, 1970). Thus, inoculated seed
should be sown on cool days, if possible. Ammendment of soil with 5 % (w/vol)
montmorillonite, fly ash or haematite has been reported to protect rhizobia from lethal effects
of high temperatures (Lowendorf, 1980).
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The optimum temperatures for growth in culture vary among strains and species; values
between 27-39°C have been noted. The maximum temperatures are generally 35-39°C, but
proliferation may take place up to 42°C (Munevar and Wollum, 1981). Differences in growth
and colonizing abilities probably explain why some strains are more active in nodulating
grain legumes at low temperatures and others are more active even at higher temperatures
(Weber and Miller, 1972).
2.7.1.3 Soil pH (Acidity and Alkalinity)
Most legumes require neutral or slightly acidic soils (Bordeleau and Prevost, 1994) for normal
growth and development. Under acidic-soil conditions legumes fail to nodulate and this is
common, especially in soils with pH less than 5 (Raza et al., 2001).
Approximately 25 % of the world's agricultural soils are acidic (Munns, 1986). Most of the
naturally acidic soils in the world are found in the tropics. This is due to the high rainfall, low
evaporation rates, leaching of cations and high biological activity (Jayasundara et al., 1998)
associated with the tropics.
Acid soils reduce plant growth and are often not nutritionally balanced. Acid soils are mostly
associated with deficiencies in phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg),
Molybdenum (Mo), copper (Cu) and cobalt (Co) (von Uexkull and Mutert, 1995), and also toxic
concentrations of aluminum (Al), hydrogen (H), and manganese (Mn) (Helyar, 1987; O'Hara et
al., 1988; Sadowsky and Graham, 1998).
2.7.1.3.1 pH effects on free-living rhizobia in the soil
The survival and persistence of rhizobia in soils is affected by soil acidity (Bottomley 1992;
Ibekwe et al., 1997). Slow growing Bradyrhizobium strains are because they produce alkali
reactions in soils (Correa and Barneix, 1997), are generally more acid tolerant than fast-growing
strains of rhizobia. Thus the alkali they produce modifies the pH of their immediate
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surroundings (Sylvester-Bradley et al., 1988). However, different levels of acid tolerance
among the different Bradyrhizobium species exist (Graham et al., 1994; van Rossum et al.,
1994; Bayoumi et al., 1995; Raza et al., 2001).
Low soil pH decreases rhizobial survival, growth, population size and even strain diversity
(Munns, 1965; Sadowsky and Graham, 1998; McInnes et al., 2004). According to Munns and
Keyser (1981), low levels of rhizobium now Bradyrhizobium and in some cases complete
absence may occur at pH below 4.5. Many active nitrogen fixers fail to survive in a sterile soil
at pH 5.2 (Lowendorf et al., 1980). Low soil pH affects the spatial distribution of indigenous
rhizobia as well (Munns and Keyser 1981). The lower number of rhizobia that are present under
low soil pH reduce the possibility of successful infection and ultimately reduce nodulation
(Whelan and Alexander, 1986).
Low soil pH can affect aspects of the nodulation process other than rhizobial population growth
(Evans et al., 1980) of RNB.
In some low pH soils, viable populations of rhizobia are known to exist (Graham and Parker,
1964; Dilworth et al., 2000; Howieson et al., 2000) in protected niches (Thornton and Davey,
1984; Wood et al., 1984; Lindstrom and Myllyniemi, 1987; Wood and Shepherd, 1987; Slattery
et al., 1992; Gemell et al., 1993b; Howieson et al., 2000; Watkin et al., 2000).
2.7.1.3.2 pH effects on symbiotic communication, attachment and infection thread
formation
These can be from indirect effects such as metal toxicity (Reeve et al., 2002).Under acidic
conditions of e.g. pH < 5.0, capacity of root exudates from seedlings to induce nodA is reduced.
Richardson et al. (1988) reported that expression of nod genes is inhibited by high aluminium
ions in solution. However, some legumes are able to tolerate Al toxicity (Howieson et al., 1992).
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The decreased growth rate of rhizobia in acid soils is likely to contribute to delayed colonisation
of the root hairs. This is critical, since the size of the rhizobial population directly influences
the concentration of Nod factors (Richardson and Simpson, 1989), and the root hairs are only
receptive to infection (Bhuvaneswari et al., 1981; Bowra and Dilworth, 1981; Wood et al. 1984;
Richardson et al. 1989) only for a brief moment.
Low pH affects the stability of rhizobia binding to roots as this causes desorption of those
previously bound (Caetano-Anolles et al., 1989). The adsorption of rhizobia to roots of legumes
dependends on the presence of divalent cations such as Ca2+ which are mostly present at
neutral to near neutral pH (Caetano-Anolles et al., 1989). Most of these cations are absent
under low soil pH conditions.
Two strategies that have been adapted to solve the problem of soil acidity in tropical soils are
liming of acid soils and selecting acid tolerant varieties of legumes and strains of rhizobia. Very
few data have been documented on the effects of high pH on rhizobial growth, nodulation or
legume growth (Bordeleau and Prevost, 1994).
Mengel and Kamprath, (1978) reported on the effect of liming acid soils (pH 3.4-4.25) on
nodule initiation and development in soybean. Soils with pH below 4.5-4.8 after liming were
found not to nodulate. The researchers therefore concluded that pH in the range 4.5-4.8 is
critical for nodule initiation and development in the soils. Lime application increases the
nodulation of some rhizobial species more than the nodulation some other species. In acid soils
lime application is usually more beneficial than mineral nitrogen application (Andrew, 1976).
However, high levels of lime application that results in raising the pH of a soil by 1, can have
deleterious effects on plant growth (Kennelly et al., 2012).
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2.7.1.4 Phosphorus content and availability.
Phosphorus is the second most limiting nutrient for plant growth in tropical soils (Schachtman
et al. 1998). Phosphorus is needed by plants right from germination to seed maturity
(Marschner, 1993). During flowering and seed formation, most of the absorbed P is translocated
from leaves to the fruits and seed regions depending on the availability of the nutrient
(Marschner, 1993). Although tropical soils have total P, phosphorus deficiency is a major
fertility problems in tropical agriculture (Miller and Ohlrogge, 1957; Bieleski, 1973; Fox and
Kang, 1977). Most tropical soil solutions contain less than 0.1 ug P mL-1 (Bieleski, 1973; Fox
and Kang, 1977). Factors and mechanisms that affect phosphorus availability in tropical soil
solutions have been discussed (Uehara, 1977; Fox and Searle, 1978; Velayutham, 1980; White,
1981; Mokwunye et al 1986; Torrent, 1987; Owusu-Bennoah and Acquaye, 1989; Pena and
Torrent, 1990; Warren, 1992; Owusu-Bennoah et al. 1997; Abekoe and Sahrawat, 2001).
There are two different forms of available phosphorus existing in soils which are dependent on
the soil’s pH. These are H2PO4- and HPO42-. At near neutral pH, both forms of the
orthophosphate ions are equally represented in terms of proportionality. In acid soils, H2PO4- is
the dominant ion in solution (almost 100 % at pH 4-6) whereas in alkaline soils, the HPO42dominates (about 80 % at pH 8 with the remaining 20 % being H2PO4-) (Black, 1968). A
continuous renewal of P in the solution that is in contact with the roots of plants is needed for
P supply to meet the total P demand of growing plants.
2.7.1.4.1 Addressing the constraint of phosphorus availability in Tropical soils
Increasing the pH of the soil by liming reduces the concentration of Al and Fe in the soil solution
thereby decreasing P adsorption (Fox and Searle., 1978). Although liming increases pH in soils,
agricultural liming usually involves a consideration of the pH range that plants are normally
grown. Thus agricultural liming may neither increase the solubility and hence the availability
of P nor does it decrease adsorption of P (Fox and Searle., 1978). Lime application must always
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be accompanied with adequate phosphorus fertilization to achieve maximum results. Therefore,
application of substantial amounts of P fertilizer (Fox and Kang, 1977) is required for optimum
plant growth and adequate food production (Sanchez and Buol, 1975; Cassman et al., 1981;
Date et al., 1995) in tropical agricultural systems.
2.7.1.4.2 Phosphorus requirements for nodulation and nitrogen fixation
Nodulation and the rate of N2-fixation are largely dependent on the availability of phosphorus
(Singleton et al., 1985; Leung and Bottomley, 1987; Saxena and Rewari, 1991). As soil organic
matter reserves and hence the supply of available nitrogen is reduced, nodulation and the
potential rate of N2-fixation will increase as long as other factors mostly phosphorus are not
limiting (Kahindi et al., 1997).
Soybean depending on nitrogen fixation for N has 47 to 75 % higher P demand than when
fertilizer nitrogen had been supplied (Cassman et al. 1981). Actively growing nodules have
been found to have high phosphorus content (Bonetti et al., 1984) and has therefore been
suggested that the amount of phosphorus required by the nodules probably forms a significant
sink in relation to the rest of the plant (Qin et al., 2012).
It has been widely reported in literature that high soil nitrogen delays or inhibits nodulation and
nitrogen fixation (Franco, 1977). However, there are indications adequate P in soils induces
nodulation even in the presence of inhibitory nitrogen levels (Gentili and Huss-Danell, 2002;
Gates and Wilson, 1974). Gentili and Huss-Danell (2002) have, therefore, concluded that N: P
ratio is important for nodulation (Wall et al., 2000) just as concentrations of N and P.
2.7.1.5 Nitrogen Availability
In soils low in available nitrogen, nodules of pigeonpea and soybean are normally initiated
within 6 days of planting and are visible by 9 days within a few centimetres of the soil surface
(Eaglesham et al., 1983). High rates of mineral nitrogen have been documented to substantially
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reduce nodule formation and inhibit nitrogen fixation eventually (Danso et al., 1992; Peoples
and Griffiths, 2009). According to Schilling et al. (2006) and Gavrichkova and Kuzyakov
(2009), nitrate (NO3-) reduction and assimilation is high and costly when carried out in plants.
Thus compared to the only 14 % of total respiratory energy (15 moles ATP) needed for
assimilating N supplied as NH4+, as much as 23 % (5 % for absorption, 15 % for reduction and
3 % for actual assimilation) of total respiratory energy (20 moles ATP) is needed for
assimilating N supplied as NO3- (Salsac et al., 1987; Bloom et al., 1992). However, the 28-32
moles of ATP required by nitrogenase to reduce 1 mole N2 or the 12 g of glucose that is required
for fixing 1 g N2 to NH3 (Evans et al., 1980) indicates that the N2 fixation process together with
the assimilation of the end product is high and costly in terms of energy (Al-Niemi et al., 1997).
Considering the energy requirements, plants will prefer mineral N to fixing N2 from the
atmosphere when presented with these two options. When the N supplied by mineral N is
enough to meet the total N requirement of the legume, nodulation is completely inhibited.
Several researchers have reported that the inhibition process is systemic.
According to Harper (1987) and Streeter (1988) the effects of mineral N inhibition is evident
in several stages of the symbiotic process resulting in decreased number of nodules, dry weight
of nodules and N2 fixation activity. In actively growing well nodulated legumes the supply of
mineral N to meet the total N requirement of a legume results in feedback inhibition of nitrogen
fixation by products of nitrate metabolism such as glutamine (Neo and Layzell, 1997),
asparagine (Bacanamwo and Harper, 1997), reduced supply of carbohydrate to nodules for
nitrogenase activity (Streeter, 1988; Vessey and Waterer, 1992) as well as decreased O2
diffusion into nodules which often restricts the respiration of bacteroids (Gordon et al., 2002).
Under such conditions nitrogenase activity is completely halted and no further nitrogen fixation
occurs resulting in the senescence of the nodules formed.
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2.7.2 Biological Factors
2.7.2.1Presence of rhizobia
Rhizobia are facultative symbionts that have adapted to persist for long periods in soils, in a
free-living state, in the absence of a suitable legume (Sanginga et al., 1994; Graham, 2008).
Their populations generally increase in upon the introduction of a host legume.
The ability of rhizobia to survive in, grow and eventually colonise a soil depends substantially
on the physical and chemical characteristics of the soil (Bushby, 1982). To enable their
survival and growth, rhizobia need to access adequate concentrations of mineral and organic
nutrients from the soil to sustain their metabolic processes (O'Hara, 2001; Poole et al., 2008).
Agricultural soils often contain established populations of RNB and many common cultivated
legume species achieve nodulation without inoculation (Thies et al., 1991; Mpepereki et al.,
1996, 2000; Wang et al., 1999; Ballard and Charman, 2000; Sessitsch et al., 2002) though these
legumes may fix nitrogen poorly (Ballard & Charman, 2000; Denton et al., 2002; Zdor and
Pueppke, 1988).
Although many legumes can be nodulated by several species of rhizobia (Mateos et al., 2011),
the fact that a high degree of host-specificity exists between legume hosts and rhizobial species
(Thrall et al., 2000) means that loss of a single rhizobial species can result in loss of N2-fixation
by that legume.
Also, not all of the indigenous rhizobia are able to effectively nodulate cultivated legumes
(Baraibar et al., 1999). In situations where the indigenous rhizobia are not effective in
nodulating legume hosts, there is the need to introduce effective strains that can grow under the
given soil conditions and compete for nodule occupancy with the indigenous strains (Naeem et
al., 2004).
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Aside from the abiotic factors, challenges associated with living in soil include tolerance to
many biotic factors, such as grazing fauna and antagonistic micro-organisms (Bottomley,
1992).
2.7.2.2 Plant factors
Nodulation and the amount of nitrogen fixed vary according to the legume species and variety
(Zahran, 1989). Within a plant species, the amount of nitrogen fixed is directly related to (dry
matter) yield (Zahran, 1989). Leguminous plants that are adapted to extremely harsh soil
conditions can be nodulated and subsequently fix nitrogen in regions where other legumes will
not even survive. In terms of varieties, high yielding varieties are able to exhaust the soil of its
nutrients (mostly N) in no time and then enter into symbiotic association with compatible
rhizobia in order to benefit from the association (Yokota et al., 2009). On the other hand, even
in the presence of compatible rhizobia, low yielding varieties of host legumes may not enter
into any symbiotic association since a considerable portion of soil nitrogen may be taken up
(Yokota et al., 2009). Where nodulation and nitrogen fixation occur in both high yielding and
low yielding legumes, the high yielding variety will be more nodulated and derive more
nitrogen from fixation than the low yielding variety (Yokota et al., 2009).
Selecting legume species that are compatible with the indigenous soil rhizobia is very important
if success of nodulation and nitrogen fixation are to be attained.
2.8 Inoculation
Inoculation refers to the introduction of effective Rhizobium bacteria into soils with the
intention that, the introduced bacteria will infect the root hairs of seedlings leading to the
formation of nodules for nitrogen fixation. Inoculation of legume with compatible and
competent bacteria results in a large benefit-cost ratio (Hardy, 1997). The success of inoculation
is however dependent on the populations of native RNB (Mpepereki et al., 2000; Wang et al.,
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1999; Ballard and Charman, 2000; Sessitsch et al., 2002; Keyser and Li, 1992). According to
Thies et al. (1991), response to inoculation can be attained in the presence of rhizobia cells
below 10 per gram of soil.
2.9 Assessment of Nodulation and Nitrogen Fixation.
The criteria used most frequently to evaluate and compare treatments in legume experiments
are nodulation, dry matter production, amount of nitrogen and phosphorus accumulated in
shoots (Cassman, 1981; Osman, 2002).
2.9.1 Nodulation
Nodule number and nodule dry weight are used as criteria for assessing nodulation. The
reliability of this method is indicated by the fact that nodule mass is highly correlated to indices
of growth such as dry matter and nitrogen content (Brockwell et al., 1982). The use of odulation
as an indicator of effective nitrogen-fixation must be done with caution as the results can be
misleading.
2.9.2 Dry Matter Yield
Nitrogen accumulation in shoot is strongly correlated with plant growth (Legget, 1971), and the
dry matter produced by legumes has therefore been recommended for use as an index to assess
effectiveness of nodulation.
Dry matter production, is often linked with the vegetative and early reproductive growth phases
of plants which are dependent on total nitrogen uptake (Brockwell et al., 1982). In soils with
depleted N, dry matter production is mainly reliant on nitrogen fixation (Brockwell et al., 1982).
The relationship between dry matter production and nitrogen fixed is indicated by the
significantly greater dry matter accumulation of effectively nodulated plants, compared to the
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lower dry matter accumulation by ineffectively nodulated or non-nodulated plants (Singleton
et al., 1986).
2.9.3 Nitrogen
Nitrogen is essential for the growth and developments of legumes. The total nitrogen in shoots
is a commonly used index of nitrogen fixation. Correlations between total foliage nitrogen and
acetylene reduction have been reported (Jardin Freirrre, 1977; Singleton and Stockinger, 1983).
For two legumes with different nitrogen fixing capabilities, there will be more N in the shoot
of the legume with a high N fixing capability than in the shoot of the legume with a low N
fixing capability. Thus, at harvest, the N content of shoots should be a good parameter to
differentiate between legumes with different N2-fixing capabilities.
2.9.4 Phosphorus content of shoot
A major factor that limits nitrogen fixation and symbiotic interactions is the availability and
supply of phosphorus (Aono et al., 2001; Sadowsky, 2005). Phosphorus has been found to be
of higher demand by legumes depending on fixation for N nutrition than legumes receiving
nitrogen fertilisation (Graham and Vance, 2000). This could be due to the strong influence on
nodulation and nitrogen fixation by availability of P (Leung and Bottomley, 1987). Total foliage
phosphorus is commonly used as an index for estimating nitrogen fixation. There correlations
between total phosphorus and acetylene reduction (Jardin Freirrre, 1977; Singleton and
Stockinger, 1983) as increased phosphorus uptake often leads to vigorous plant growth and
subsequently higher demands for fixed nitrogen.
2.10 Measurement of BNF
In order to evaluate the nitrogen contribution of legumes to agricultural systems, it is important
to accurately measure the amount of N2 that these legumes derive from the atmosphere. There
are many proposed methods for measuring the amount of nitrogen fixed by legumes in
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symbiotic association with RNB. The methods that have been commonly used for estimating
nitrogen fixation in plants are total nitrogen difference (TND), acetylene reduction assay and
15
N isotope dilution method. The different methods have their advantages and limitations as
well (Rennie and Rennie, 1983; Danso, 1985). The method used to measure the amount of
nitrogen fixed in this study was 15N Isotope Dilution Technique
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CHAPTER THREE
3.0 MATERIALS AND METHODS.
3.1 Soil sampling
The soils used in the study were Adenta, Bekwai and Nzima series. Bekwai and Nzima series,
classified as Ferric Acrisol and Haplic Acrisol, respectively (Owusu-Bennoah et al., 2000), were
sampled from the catena at the Forest and Horticultural Crops Research Centre (FOHCREC)
Okumaning-Kade whilst Adenta series, classified as Haplic Acrisol (Dowuona et al., 2012) was
sampled from the School Farm at the University of Ghana campus, Legon. The soils were
sampled from uncultivated sites. The soils were dug from the 0-20 cm depth, bagged and
labelled. The bagged soils were later air dried, crushed to pass through a 2 mm sieve to remove
any organic debris, gravels and concretions. The sieved soil was mixed uniformly and portions
were sampled for routine analyses in the laboratory. Bekwai and Nzima series are found in the
Semi-deciduous forest agro-ecological zone, with an annual rainfall of 1400-1700 mm. The
soils have a granitic parent material as they are developed from the lower Birimian. Adenta
series on the other hand, is found in the Coastal Savannah agro-ecological zone of Ghana with
an annual rainfall of less than 800 mm. Soils in these zones are developed on red, brown
sandstone, shale. Adenta series occurs extensively on gentle middle slopes with site gradient of
1-2 %.
3.2 Physical Analyses
The physical analyses carried out on the soils are particle size analysis, bulk density and field
capacity determinations.
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3.2.1 Particle Size Analysis
The hydrometer method of Bouyoucos modified by Day (1965) was used to determine the silt
and clay contents of the soils used. Forty grams (40.0 g) of the sieved soil samples was weighed
into a dispersing bottle and 100 mL of 5 % Calgon (Sodium Hexametaphosphate) solution was
added to the weighed sample to form a suspension. The suspension was agitated using a
mechanical shaker for 2 h to disperse the various soil particles into sand, silt and clay. The
suspension was then transferred into a 1000 mL graduated sedimentation cylinder and made up
to the 1000 mL mark with distilled water. A plunger was lowered into the cylinder and moved
up and down, about 5 times to stir the suspension vigorously. Hydrometer readings were taken
by lowering the hydrometer in the suspension and the readings taken at the meniscus. The
readings were taken after 5 min (i.e. silt plus clay), and thereafter 5 h (i.e. clay). The sand
content was determined by decanting the suspension directly onto a 47 µm sieve. The decant
was discarded and the residue was washed thoroughly with tap water and then poured into a
moisture can with known weight for oven drying at 105oC for 24 h. The weight of the dried
particles (sand) was determined after oven drying and the particle distributions for the various
soil series were then computed as follows:
Clay content = hydrometer reading at 5 h = A g
Silt content = hydrometer reading at 5 min- hydrometer reading at 5 h = B g
Sand content (weight of oven dried sample i.e. Dry weight) = C g
% clay =
% silt =
% sand =
Ag
40 g
Bg
40 g
× 100
[1]
× 100
Cg
40 g
[2]
× 100
[3]
Where 40 = weight of soil sample in grams
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The distribution values were used to determine the textural class of the soils using the USDA
textural triangle presented in Appendix 1.
3.2.2 Bulk density
Bulk density was determined using the core sample method of Blake and Hartge, (1986). Core
samples were taken from locations previously selected to be representative of the entire area
where the soils for the experiments would be taken. The soil surface was cleared and a
cylindrical core sampler was gently driven into the soil far enough to fill the volume of the core
with the help of a mallet. The soil surrounding the core sampler was gently removed so that the
sampler could be removed from the soil without disturbance. The ends of the sampler were
levelled with a knife edge and thereafter, the content was emptied into labelled polybags. The
soils were then taken to the lab for bulk density determination.
In the laboratory, the content of the polybag was emptied into a clean moisture can with known
weight (W1). The moisture can together with its contents were oven dried for 72 h at 105˚C and
thereafter, the weight was taken (W2). Bulk density was calculated using the formula by Blake
(1965).
ρb (kg/m3 ) =
M
(πd2 ⁄4)h
[4]
Where
Ρb = Bulk density of soil
M= mass of soil = W2-W1
W2 = Weight in grams taken after oven drying the moisture can and its contents.
W1 = Weight in grams of empty moisture can.
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Π d2/4= area of core base
d= diameter of core
h= height of core
Π = constant=3.142
(Π d2/4) h= volume of core= volume of soil
3.2.3 Field Capacity
Five hundred (500) grams each of the 2 mm sieved soil was weighed into a pot in triplicates
and saturated with distilled water. The saturated soil was then allowed to drain for 48 h in open
air. Thereafter, sub samples of the soil were taken, weighed and oven dried at a temperature of
150 oC for 24 h. The dry weight of the soil samples was also taken after oven drying the
percentage water content at field capacity was computed as follows:
% water content =
weight of wet soil− weight of oven dried soil
Weight of the wet soil
× 100
[5]
3.3 Chemical analysis
3.3.1 Soil pH
The pH of each soil was measured electrochemically (Peech, 1965) both in water and salt with
ratios of 1:1 for soil: distilled water and 1:2 for soil: salt (CaCl2). Twenty (20) grams of sieved
soil was weighed into a 50 mL beaker and 20 mL distilled water was added to form a
suspension. The suspension was then stirred vigorously for about 30 min. The stirred
suspension was allowed to stand for 1 h to allow for the entire suspended particles to settle. The
pH meter (Pracitronic M.V 88) was standardised with standard aqueous solutions of pH 4 and
pH 7. The pH of the soil was measured after carefully and gently inserting the glass electrode
of the pH meter into the supernatant and recorded as pH in water (pHw). The process was
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repeated with 20 g of soil and 40 mL of 0.01 M CaCl2 . The reading on the pH meter was taken
and recorded as the soil pH in salt (pHS)
3.3.2 Organic Carbon
The soil organic carbon content was determined using the wet combustion method of Walkley
and Black (1934). Half a gram (0.5 g) of 0.5 mm sieved soil was weighed into a 250 mL
Erlenmeyer flask. Ten (10) millilitres of 1N potassium dichromate (K2Cr2O7) solution and 20
mL of concentrated sulphuric acid (H2SO4) were added to the content of the flask. The flask
was swirled to ensure full contact of the soil with the solution after which it was allowed to
stand for 30 min for an efficient combustion. Two hundred (200) millilitres of distilled water
and 10 mL of orthophosphoric acid were also added. The unreduced K2Cr2O7 remaining in
solution after the oxidation of the oxidizable organic material in the soil sample was titrated
with 0.2 N ammonium ferrous sulphate using 3 mL of barium diphenylamine sulphate as
indicator. A sharp change to green signified the end point of the reaction. The normality of the
Fe (NH4)2(SO4)2 was standardised using a prepared blank solution. The percent organic carbon
was calculated as:
%C =
0.3 × (10 – XN) × 1.33
W
× 100
[6]
Where % C = Percent organic carbon
X = Titre value (mL)
N = Normality of Fe (NH4)2(SO4)2
W = Weight of soil sample
0.3= 0.003 x 100
0.003= Milliequivalent weight of carbon (g)
1.33= correction factor (f)
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3.3.3 Available Nitrogen
A 10.0 g soil sample that has passed through a 2.0 mm sieve was weighed into a 100 ml
extraction bottle and 50 ml of 2 M KCl was added. The soil suspension was shaken for 20 min,
after which it was filtered through a No 42 Whatman filter paper into a clean empty plastic
bottle. A 10 mL aliquot of the filtrate was taken into a 250 mL Kjeldahl flask and 0.2 g MgO
powder was added after which 100 mL of distilled water was added to distil for ammonia (NH3).
The NH3 was distilled into 5 mL of 2 % boric acid (containing a methylene blue and methyl red
indicator mixture) in a 150 mL conical flask. Fifty mL of the distillate was collected. The
solution left in the 250 mL Kjeldahl flask was allowed to cool and 0.2 g of Devarda’s alloy was
added to reduce the NO3-N to NH4+-N. Nitrite in the sample was destroyed by the addition of
1 mL of sulphamic acid. Fifty millilitres of the distillate was collected into 5 mL of 2 % boric
acid indicator mixture in a separate conical flask. The distillate was titrated against 0.01M HCl.
The concentration of NH4+ mg L-1 soil was calculated as follows:
𝑁𝐻4+ kg −1 soil =
MHCl ×VHCl ×10−3 ×18×VKCl×1000 mg
Volume of Aliquot×Weight of soil (g)
Where:
MHCl = Molarity of the HCl
VHCl = Titre of the HCl
VKCl = Volume of KCl extractant
18 = Molecular weight of NH4+
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3.3.4 Total Nitrogen
The Kjedahl method was used in the determination of total N. Half a gram (0.5 g) of 2 mm
sieved soil was weighed into 250 mL Kjedahl flask and a tablet of a digestion accelerator,
selenium catalyst was added. This was followed by addition of 5 mL of concentrated H2SO4.
The mixture was digested until the digest became clear. The flask was then cooled and its
content transferred into a 100 mL volumetric flask. The content was made to the 100 mL mark
with distilled water. An aliquot of 5 mL of the digest was taken into a Markham distillation
apparatus. Five (5) mL of 40 % NaOH was added and the mixture distilled. The distillate was
collected in 5 mL of 2 % boric acid (H3BO3) solution. Three drops of a mixed indicator
containing methyl red and methylene blue were added to the distillate in a 50 mL Erlenmeyer
flask and then titrated against 0.01M HCl acid solution (Bremner, 1965). The % nitrogen was
calculated as:
%N =
0.01 × titre volume × 0.014 × volume of extract ×100
Sample weight (g) × volume of aliquot (mL)
[8]
Where 0.01 = Normality of HCl
0.014 = Milliequivalents of Nitrogen
3.3.5 Available Phosphorus
Available phosphorus was determined using the method of Bray and Kurtz (1945). Five grams
of 2 mm sieved soil was weighed into an extraction bottle. Fifty millilitres of Bray 1 solution
(0.03M NH4F in 0.025M HCl) was added. The suspension formed was shaken for 3 min on a
reciprocating shaker, allowed to settle and filtered through a No. 42 Whatman filter paper into
a 100 mL volumetric flask and made up to the volume. Phosphorus in the filtrate was
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determined using the molybdate-ascorbic acid colour development method of Watanabe and
Olsen (1965) as follows:
Five millilitre aliquots of the supernatant were pipetted in duplicate into a 100 mL volumetric
flask and the pH adjusted with para-nitrophenol indicator. Then after, the solution was
neutralized with a few drops of ammonium hydroxide (4M NH4OH) until the colour changed
to yellow. This was followed by addition of distilled water till a colourless solution was
observed. Reagent A was prepared by dissolving 12 g of ammonium molybdate and 0.2998 g
of antimony potassium tartrate in 250 mL of distilled water. Reagent B was prepared by
dissolving 1.056 g of ascorbic acid in 200 mL of Reagent A. The dissolved reagents were added
to 1000 mL of 2.5 M H2SO4, mixed thoroughly and made to volume in a 2000 mL volumetric
flask. Eight millilitres of Reagent B was then added to the sample solution and made to volume
in a 100 mL volumetric flask. A blank was also prepared using 5 mL of distilled water and 8
mL of reagent B. The Philips PU 8620 spectrophotometer was calibrated using 25 mg L-1
standard P solution prepared in the same manner as above. Phosphorus in the solution was
determined by reading the resultant colour intensity on the Philips PU 8620 spectrophotometer,
at a wavelength of 712 nm. The available P concentration in the soil sample was read and
calculated using the spectrophotometer reading as follows
P (%) =
spectrophotometer reading (𝑚𝑔𝐿−1 )× total volume of extract
volume of aliquot × weight of soil sample × 106
× 100
[9]
3.3.6 Total Phosphorus
Total phosphorus was determined by digesting 2 g of 0.5 mm sieved soil with 25 mL of a
mixture of concentrated HNO3 and 60 % HClO4 in the ratio of 2:3. The digestion was continued
until white fumes of HClO4- ceased. The digest was cooled, diluted with distilled water and
then filtered into a 100 mL volumetric flask using a No. 42 Whatman filter paper. The volume
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was brought to the 100 mL mark with distilled water. Phosphorus in the filtrate was measured
by colour development and read on Philips PU 8620 spectrophotometer as described in section
3.3.5
3.3.7 Exchangeable bases and Cation Exchange Capacity (CEC) Determination
3.3.7.1 Extraction of exchangeable bases.
Ten (10) grams of soil was weighed into a 200 mL extraction bottle and 100mL of 1N
ammonium acetate (NH4OAc) solution buffered at pH 7.0 was added. The bottle and its content
were placed on a mechanical shaker and shaken for 1 h, and thereafter centrifuged at 3000 rpm
for 20 min. The supernatant solution was then filtered through a No. 42 Whatman filter paper.
The filtered solutions (aliquots) were used for the determination of Ca, Mg, K and Na.
3.3.7.2 Calcium.
To a 10 mL aliquot of the sample solution, 10 mL of 10% KOH and 1mL triethanolamine (TEA)
were added. Three drops of 1M KCN solution and a few crystals of cal-red indicator were then
added after which the mixture was titrated with 0.02N EDTA solution from red to blue end
point. The titre value was used in the calculation of calcium as shown below.
Ca 𝑐𝑚𝑜𝑙𝑐 𝑘𝑔−1 =
Titre value × N × Vol.of extract × 100)
Aliquot × Weight of soil
[10]
Where N = Normality of EDTA
3.3.7.3 Magnesium.
To a 10 mL aliquot of the sample solution, 5 mL of ammonium chloride-ammonium hydroxide
buffer solution was added followed by 1mL of triethanolamine. Three drops of 1M KCN
solution and a few drops of Eriochrome black T solutions were added after which the mixture
was titrated with 0.02 N EDTA solution from red to blue end point. The end point titre value
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determines the amount of calcium and magnesium in the solution. The titre value of magnesium
was then determined by subtracting the value obtained for calcium above from the new titre
value obtained. The titre value of magnesium was then used for the calculation of the
concentration of magnesium (Mg) as shown below.
Mg 𝑐𝑚𝑜𝑙𝑐 𝑘𝑔−1 =
Titre value × N × Vol.of extract × 100)
Aliquot × Weight of soil
[11]
Where N = Normality of EDTA
3.3.7.4 Potassium
The flame photometer was standardized such that 10 mg/kg of K gave 100 full scale deflections.
The flame photometer after standardization was used to determine the concentration of
potassium in the aliquot. The result was used in the calculation of the amount of potassium
present in the soil as shown in the formula below.
K 𝑐𝑚𝑜𝑙𝑐 𝑘𝑔−1 =
R × Vol.of extract × 100)
[12]
Weight of soil ×39.1
Where,
R is the flame photometer reading (ppm)
39.1 = Atomic weight of K
3.3.7.5 Sodium
The flame photometer was standardized in a way that 10 mg/kg of Na gave 100 full scale
deflections. After the standardization of the photometer, the concentration of sodium in 10mL
aliquot was determined. The result was then used in the calculation of the amount of sodium
(Na) present in the soil as shown by the formula below.
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Na 𝑐𝑚𝑜𝑙𝑐 𝑘𝑔
−1
=
R × Vol.of extract × 100)
[13]
Weight of soil ×23
Where,
R (ppm) = flame photometer reading
23 = Atomic weight of Na
3.3.7.6 Cation Exchange Capacity (CEC)
The residue after filtration in section 3.3.7.1 was immediately leached with 25 mL portions of
methanol into empty plastic bottles. The soil was leached again with 25 mL portions of
acidified 1M KCl. Each portion was added at a time and allowed to pass through, before adding
the next portion. Ten millilitres of the leachate was transferred into a Kjedahl flask and 10 mL
of 40 % NaOH was added and then distilled. The distillate was collected into 5 mL of 2 % boric
acid and an aliquot was titrated against 0.01M HCl. The ammonium ion concentration in the
filtrate was determined and the CEC of the soil in cmolckg-1 soil estimated.
3.3.8 Exchangeable acidity and Effective Cation Exchange Capacity (ECEC)
Determination
3.3.8.1 Extraction of exchangeable acidity (H+ and Al3+).
Ten (10) grams of soil was weighed into a 100 mL extraction bottle and 50 mL of 1M KCl
solution was added. The bottle and its content were placed on a mechanical shaker and shaken
for 30 min. The soil suspension was then filtered through a No. 42 Whatman filter paper into
an empty clean bottle. Twenty five millilitre aliquot was pipetted into a 100 mL conical flask
and 2-3 drops of phenolphthalein indicator was added for titration to a permanent pink end point
against 0.01M NaOH. The titre value was recorded as titre for both H+ and Al3+. Ten millilitres
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of NaF was added to the solution at the endpoint and back titrated against 0.01M HCl until a
colourless end point was reached. The titre was recorded as the titre for Al3+.
3.3.8.2 Effective Cation Exchange Capacity (ECEC)
The Effective Cation Exchange Capacity is equal to the sum of the exchangeable Ca2+, Mg2+,
Na+, K+, H+, and Al3+. (i.e. Ca2++ Mg2++ Na++ K++ H++Al3+)
3.4 Biological Analysis
3.4.1 Estimation of the populations of rhizobia in the soils using the Most Probable
Number (MPN) plant infection technique.
The populations of indigenous bradyrhizobia in the soils capable of nodulating the test legumes
were estimated by the Most Probable Number (MPN) plant infection assay (Vincent, 1970)
using a modified Leonard jar assembly by Ferreira and Marques (1992). The assembly was
composed of a plastic cup tapered to a similar cup at the bottom. The cup containing the rooting
medium (6 M HCl washed sand) was inserted into a similar plastic cup containing 100 mL of
N free nutrient solution (Somasegaran and Hoben, 1994). The rooting medium was irrigated
with a cotton wick connecting the upper and the lower units (containing the nutrient solution).
Thereafter, the whole assembly was autoclaved to get rid of microorganisms. The legume seeds
were surface sterilized in 70 % ethanol for 3 min and rinsed thoroughly in several changes of
sterile distilled water (Somasegaran & Hoben, 1994). The seeds were pre-germinated on moist
filter paper in petri dishes until the radicles were about 2 cm long. A pair of sterilized forceps
was used to pick up the sterilized seeds and plant at two seedlings seed per growth pouch with
the radicle facing downwards. The holes were deep enough to accommodate pre-germinated
seeds 0.5 cm below the surface. The assemblies were randomly arranged in a greenhouse. Ten
fold serial dilutions up to level 5 (10-1, 10-2, 10-3, 10-4, 10-5) were prepared for each of the soils
using yeast extract mannitol broth as diluent, and used as inoculum. One millilitre of the
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inoculum was used to inoculate the seedlings in triplicates per every dilution level. The plants
were assessed for the presence of nodules 6 weeks after planting and the most probable number
of rhizobia cells per gram of soil was calculated (Vincent, 1970). At harvest, the total number
of nodulated units was obtained by summing up the nodulated units at each dilution level.
Uninoculated controls were used to check for sterile conditions. The MPN was calculated using
the formula:
MPN =
m ×d
[14]
v
Where: m is the most likely number from MPN table (Alexander, 1965).
d is the lowest dilution in the series and
v is the aliquot used for inoculation (Somasegaran & Hoben, 1994).
3.5 Greenhouse Experiment.
3.5.1 Test crops used
The test crops used were soybean (glycine max cultivar Anidaso), pigeonpea (Cajanus cajan
cultivar ICPL 88034), cowpea (Vigna unguiculata cultivar black eye) and maize (Zea maiz
Cultivar Obaatampa used as a reference plant).
3.5.2 Nitrogen and Phosphorus Response Experiment
In all, three greenhouse experiments were conducted in this study. The experiments were
conducted in plastic pots (14.5 cm high, 16.3 cm wide at the top and 11.2 cm wide at the base).
Three openings were created at the base of the pots and covered with cotton wool. The pots
were filled with 2 kg of sieved soil and then after, subjected to the field bulk densities of the
soils. Water was applied at field capacity and then the pots were allowed to stay for two days
before seeds were sown into them. The pots were placed in basins with water serving as
reservoir. Water supplied in the basins was taken up through the openings created at the base
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of the pots. The first experiment was conducted to assess the response of soybean and pigeonpea
to nitrogen and phosphorus fertilizer application in the Bekwai and Adenta soils. The
counteracting effect of P on N inhibition of nodulation as well as N toxicity on plant growth
were also assessed. In one treatment, (NH4)2SO4 was applied alone at rates 0, 40, 80, 120, 160
and 200 kg N/ha. In another treatment, triple super phosphate (TSP) was first applied alone at
rates 0, 40, 80, 120, 160 and 200 kg P/ha then in combination with 100 kg N/ha as another
treatment. The second experiment was conducted to assess the effect of P on nitrogen fixation
in the Adenta soil. Phosphorus was applied at rates 0, 40, 80, and 120 kg P/ha. Nitrogen in the
form of (15NH4)2SO4 which contained 10.93 15N % natural abundance was applied at a rate of
10 kg N/ha in two splits (5 days after germination and three weeks after germination) to the
pots to supply 1.5 mg N/pot. The last experiment was carried out to investigate the effect of P
on the diversity of the indigenous bradyrhizobia that nodulated soybean, pigeonpea and cowpea
in the Adenta, Bekwai and Nzima soils. Phosphorus was applied at 0 and 80 kg P/ha rates. The
experiments were carried out one at a time. All the experiments were arranged in a completely
randomised design with 4 replications. Four seeds were planted into each pot and later thinned
to two, 4 days after emergence. The plants were kept in a greenhouse and watered daily (such
that soil moisture was kept close to field capacity) for eight (8) weeks after which they were
harvested for observations and further investigations.
3.5.3 Harvesting
The plants were allowed to grow for 8 weeks after which they were harvested. In most cases,
nodules were selected for rhizobia isolation and characterisation. Nodule number and dry
weight of nodules were taken as well. The harvested shoots were oven dried at 780C for 72 h to
attain constant weight and thereafter the dry weights were taken. The dried shoots were ground
using an electric grinder after which samples were taken for total nitrogen and phosphorus and
15
N analyses.
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3.5.4 Isolation of N2-fixing bacteria (rhizobia) from root nodules.
Nodules were carefully detached from washed roots of healthy green legumes as described by
(Vincent, 1970). The detached nodules were carefully blotted dry with tissue and immersed
momentarily in 75 % ethanol followed by another 3 min exposure to 0.1 % acidified HgCl2
solution. After rinsing for 7 times with sterile de-ionized water, each nodule was dissected and
the coloration of the internal bacteroid tissue noted. The dissected nodule was crushed in a drop
of sterile de-ionized water, and a cooled sterile loop was used to pick from the turbid suspension
formed and streaked unto yeast-mannitol agar (YMA) plates as described by Beck et al. (1993).
The plates were incubated at 28°C and the growth was monitored after day one for fast and
slow growing rhizobia. Isolated single colonies were selected and re-streaked unto Congo red
YEM for purification and thereafter authenticated (Vincent, 1970; Dakora and Vincent, 1984).
3.5.5 Estimation of N2 fixed
The % 15N atom excess in the fixer and non-fixer were analysed from KULEUVEN research
and development laboratory in Belgium. From comparisons of the 15N contents of the fixer and
the reference crop, the % Ndfa in fixing plants were calculated based on the formula established
by Fried and Middelboe (1977).
The total N in shoots was analysed for 15N, and the percentage of N derived from the atmosphere
(%Ndfa) by the legume was calculated using the equation:
% Ndfa = 1 −
% Ndff (fixer)
% Ndff (non−fixer)
× 100
[15]
Where;
% Ndfa = percent N derived from the atmosphere by the fixing plant
% Ndff (fixer) = percent N derived from the 15N labelled fertilizer by the fixing plant.
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% Ndff (non-fixer) = percent N derived from the 15N labelled fertilizer by the non-fixing plant.
Actual nitrogen fixed = % Ndfa x shoot total nitogen of the fixing plant
[16]
3.6 Statistical Analysis
The data collected from the various experiments were subjected to general Analysis of Variance
and the means obtained were compared by LSD 5 % level of significance using GenSTAT (9th
edition) software. Microsoft Excel program was used to generate graphs for data presentation.
3.7 Molecular Characterisation
Nodules were selected to be representative of the total number of nodules collected from
soybean, pigeonpea and cowpea in Adenta, Bekwai and Nzima soils. In all about 150 strains of
Bradyrhizobium were isolated from the selected nodules. Total genomic DNA was extracted
for 120 isolates and also the reference strain USDA 110. The extracted genomic DNAs were
used for DNA finger printing. Two sets of primers were used for the PCR amplifications. One
set of the Primers for Bradyrhizobium was RPO4 (random) and RPO1 (specific, targeting the
conserved nif gene promoter region) (Richardson et al., 1995). The other set of primers used
were those targeting the 16S, 23S and ITS conserved regions of Bradyrhizobium. Isolates from
fertilised treatments were designated F whereas those from unfertilised treatments were
designated U.
3.7.1
DNA Extraction
Total genomic DNA was extracted using the Qiagen DNeasy plant mini DNA extraction kit.
The rhizobial isolates were grown in YEM broth in an incubator shaker at 150 rpm at 28°C for
72 h. About 1-2 mL of rhizobial cultures were centrifuged at 8500×g (5950 rpm) for 10 min
and the supernatant discarded. The cell pellets were re-suspended in 400 µL of preheated AP1
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buffer (lysis buffer), vortexed and incubated at 65oC for 15 min in a water bath. The tubes were
inverted every 5 min during the incubation period. The cell pellets were added with 130 µL of
AP2 buffer (precipitation buffer), vortexed and incubated on ice for 5 min. The lysate was
transferred into a DNA Mini spin column placed in a 2 mL collection tube and centrifuged for
5 min at 20,000×g (14,000 rpm). The flow-through fraction was transferred into a new tube and
1.5 volumes of AP3/E was added and mixed by pipetting 650 µL of the mixture and transferred
into a DNeasy Mini spin column in a 2 mL collection tube and then centrifuged for 1 min at
6000×g (4200 rpm), after which the flow-through was discarded. Five hundred microliters of
AW buffer was added and centrifuged for 2 min at 20,000×g (14,000 rpm). the spin column
was carefully transferred into a new 2 mL micro centrifuge tube, and 100 µL of AE buffer was
added for elution. The mixture was incubated at room temperature for 5 min, centrifuged at
6000×g (4200 rpm) for 1 min. The column was discarded and the DNA stored at 4C for short
term use and -20C for long term use.
3.7.2
PCR Amplification of Genomic DNA using RPO1 and RPO4 Primers
Total genomic DNA of the bradyrhizobial isolates were amplified using the primers, RPO1 and
RPO4. Amplification reaction was carried out in a 12.5 μL final reaction volume containing 1
μL of 12.5 mM MgCl2, 1.25 μL of ×10 buffer, 0.25 μL of dNTPs, 0.25 μL of Taq polymerase,
1 μL of primer, 1.5 μL of template DNA and 7.25 μL of water. Polymerase chain reaction (PCR)
amplifications were carried out in a BOI-RAD iCycler system with an initial denaturation of
92°C for 30 s, followed by 35cycles of denaturation (30 seconds at 94°C), annealing (2 min at
40°C), and extension (90 seconds at 78°C); followed by a final extension at 72oC for 3 min.
The PCR products were examined on a 2 % agarose gel pre-stained with ethidium bromide in
1×Tris-acetate EDTA (TAE) buffer. The gels were run for 120 min at 90 V and photographed
under UV illumination in a GeneFlash (Syngene BIO Imaging) unit.
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3.7.3
PCR Amplification of 16S-23S Intergenic Spacer (ITS) and 16S rDNA Gene
Polymerase chain reactions (PCR) of the 16S rDNA, 23S rDNA and the 16S-23S rDNA
internally transcribed (ITS) conserved regions were performed with the primer sets; 16SF (5′AGAGTTTGATCCTGGCTCAG-3′) and 16SR (5′-AAGGAGGTGATCCAGCCGCA-3′) ITS
149072F
(5′-TGCGGCTGGATCCCCTCCTT-3′),
23SF
and
ITS
13238R
(5′-
CCGGGTTTCCCCATTCGG-3′). Amplification reactions were performed in a 25 µL volume,
containing 2 µL MgCl2(25mmolL-1), 0.5 µL of dNTPs, 2.5 µL of 10× buffer, 0.5 µL Taq
polymerase, 12.8 µL of H2O, 2.0 µL of each primer and 2 µL of template DNA. The thermal
profile used was an initial denaturation step at 95 °C for 1min, 35 cycles consisting of 1 min
denaturation at 94 °C, 1 min of primer annealing at 50 °C and 2min of extension at 72 °C, plus
a 3min final extension at 72 °C.
3.7.4 Cluster Analysis
Gel electrophoresed images were analysed and scored for presence (1) and absence (0) of band
using the PyElph version 1.4 software. The patterns obtained from the PCR using
oligonucleotide primers RPO1 and RPO4 were combined for cluster analysis. A simple
matching coefficient was calculated to construct a similarity matrix and the Unweighted Pair
Group Mean Arithmetic Method (UPGMA) algorithm was used to perform hierarchical cluster
analysis and to construct a dendogram by using NTSYS-pc package V.2.1 (Rohlf, 1998) at a
matrix of 1. Genetic comparisons for the isolates were carried out and clusters formed at 80 %
similarity were considered different with isolates within a particular cluster being genetically
similar.
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3.7.5 Diversity Indices
The Shannon-Weaver (1949) diversity index and Pielou (1975) evenness index were calculated
for every dendogram generated and were compared to ascertain where a greater diversity among
isolates occurred. These Indices of diversity (H′) were estimated based on the number of
clusters formed at 80 % similarity.
3.7.5.1 Shannon- Weaver diversity index.
The Shannon-Weaver (1949) diversity index was calculated from the formulae below
H ′ = − ∑𝑛𝑖−1 𝑃𝑖 𝑙𝑛𝑃𝑖
[17]
Where Pi is the proportion of individuals found in clusters i. For a well-sampled community,
this proportion is given as Pi = ni/N, where ni is the number of individuals in cluster i and N is
the total number of individuals in the dendogram. Since by definition the p is between zero and
one, the natural log makes all of the terms of the summation negative, which is why the inverse
of the sum is taken.
3.7.5.2 Pielou evenness index
The Pielou (1975) evennesss index was calculated from the formulae below:
′
J = H ⁄lnS
[18]
where H′ is the Shannon–Weiner index and S is the total number of clusters per soil at 80%
similarity level.
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CHAPTER FOUR
4.0 RESULTS
4.1 Physical and chemical properties of soils used.
The Adenta soil had the highest proportion of sand (62 %) followed by the Nzima soil (33 %)
and then the Bekwai soil (23 %) (Table 1). Among the three soils, the soils from the semideciduous forest contained higher silt (25 %) than the soil from the coastal savannah with 13 %
silt. The Bekwai soil contained the most clay (52 %), while percent clay content in the Adenta
series (25 %), was the lowest (Table 1). From the textural analysis, the Adenta soil was
classified as a sandy clay loam using the USDA textural triangle (Appendix 1) with the Bekwai
and Nzima soils being classified as clay. Bulk density was highest in the Bekwai soil (1.49 Mg
m-3) followed by the Nzima soil (1.42 Mg m-3) and then the Adenta soil (1.35 Mg m-3). The pH
analyses conducted on the soils show that the Bekwai soil had the lowest pH in water (5.5)
followed by the Nzima (5.6) and then the Adenta (6.2). A similar trend was observed for CaCl2
determined pH. In all cases the pH determined in CaCl2 was higher than the pH determined in
water The Nzima soil contained the highest organic carbon (33.5 g kg-1) followed by the Bekwai
(31.9 g kg-1) while the Adenta soil contained the lowest organic carbon (23.1 g kg-1). The total
nitrogen values obtained for the Bekwai and Nzima soils were higher than that for the Adenta
soil with the Bekwai soil being the highest (Table 1). The Adenta soil, although recorded the
lowest total nitrogen, had the highest nitrogen in soil solution. The Bekwai and Nzima soils
recorded lower available phosphorus and available nitrogen compared to that for Adenta soil
(Table 1). The cation exchange capacity (CEC) was highest in the Nzima soil (19.5 cmolc kg-1)
followed by the Bekwai soil (18.7 cmolc kg-1) while the Adenta soil recorded the lowest CEC
(7.0 cmolc kg-1). The effective CEC (ECEC) was found to be highest in the Nzima soil (7.47)
and lowest in the Adenta soil (5.25). The high clay content of the soils from the semi-deciduous
forests together with a high organic carbon content accounted for the high differences in their
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CEC and ECEC. The CEC and ECEC data from the coastal savannah soil with a lower organic
carbon content and a lower clay content as well did not reveal such great difference compared
to the forest soils (McCauley et al., 2003).
Table 1. Physical and Chemical properties of Adenta, Bekwai and Nzima soils.
Soil Properties
Adenta
Bekwai
Nzima
Sand (%)
62
23
33
Silt (%)
13
25
25
Clay (%)
25
52
42
Texture
SCL
Clay
Clay
Bulk Density (Mg m-3)
1.35
1.49
1.42
pH H2O (Soil: Water, 1:1)
6.2
5.5
5.6
pH CaCl2 (Soil: CaCl2, 1:2)
5.7
4.3
4.4
Organic Carbon (g kg-1)
23.1
31.9
33.5
-1
Total N (g kg )
0.98
1.96
1.62
-1
304.56
270
233.28
-1
8.75
2.79
2.54
Total P (mg kg )
97.00
95.75
83.5
Cation Exchange Capacity (cmolckg-1)
7.1
18.7
19.5
Ca
2.9
4.1
4.8
Mg
1.5
1.6
1.47
K
0.3
0.7
0.61
Na
0.11
0.07
0.02
Exchangeable Al3+ (cmolckg-1)
0.1
0.2
0.13
Exchangeable H+ (cmolckg-1)
0.34
0.24
0.44
Effective CEC (cmolckg-1)
5.25
6.91
7.47
Available N (mg kg )
Available P (mg kg )
-1
Exchangeable bases (cmolckg-1)
SCL: Sandy Clay Loam
CEC: Cation Exchange Capacity
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4.2 Populations of bradyrhizobia nodulating soybean and cowpea in Adenta, Bekwai and
Nzima series.
The results from the population study using the Most Probable Number (MPN) plant infection
technique revealed the presence of bradyrhizobia in all the soils studied (Table 2). The
population sizes of indigenous bradyrhizobia nodulating the various legumes in the different
soils varied widely ranging from 0.7×101 to 7.8×103 cells/ g soil. The highest population of
soybean nodulating Bradyrhizobium was recorded in Nzima series (4.5 × 102 cells/g soil) and
the lowest in Bekwai series (0.7×101 cells/g soil). Ninety two cells of soybean nodulating
Bradyrhizobium were present in each gram of the Adenta soil (Table 2). Cowpea was used as a
control and nodulated in all the soils. The size of Bradyrhizobium nodulating cowpea in Bekwai
series was the highest. The population of cowpea nodulating Bradyrhizobium present in the
soils is ranked as follows Bekwai (7.8×103 cells/g soil) > Nzima (9.2×102 cells/g soil) > Adenta
(9.2×102 cells/g soil). In all the soils, the population of the Bradyrhizobium nodulating cowpea
was higher than that of the Bradyrhizobium nodulating soybean.
Table 2. Populations of indigenous soybean and cowpea bradyrhizobia estimated by the
Most Probable Number (MPN) technique.
Legume Host
Soybean
Cowpea
Most Probable Number technique (cells/g soil)
Soil series
Adenta
Bekwai
Nzima
1
1
9.2 × 10
0.7× 10
4.5 × 102
6.8 × 102
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9.2 × 102
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4.3 Responses of soybean and pigeonpea to nitrogen and phosphorus fertilizer application
in Adenta and Bekwai series.
4.3.1 Phosphorus fertilizer application and nodulation of soybean and pigeonpea.
Although the application of P resulted in higher nodulation in pigeonpea grown in the Adenta
soil beyond the 60 nodules/plant observed for the control, the differences were not significant
(P > 0.05) up to the 120 kg P/ha rate. Further application of P to 160 kg P/ha, however, resulted
in a non-significant (P > 0.05) decrease in nodulation whereas application of 200 kg P/ha
resulted in a significant (P < 0.05) decrease in nodulation when compared to the control. In the
case of soybean, application of P up to 120 kg P/ha gave no significant (P > 0.05) increases in
number of nodules formed compared to the control (Fig. 1). Significant (P < 0.05) increases in
the nodules formed on soybean were, however, observed with phosphorus application at rates
of 160 kg P/ha and 200 kg P/ha in the Adenta soil over the control. About 4-fold and 6-fold
increases in nodule numbers compared to the control were recorded when soybean was
fertilized with 160 kg P/ha and 200 kg P/ha, respectively in the Adenta soil. The number of
nodules recorded for soybean increased from 6 in the control to 40 when 200 kg P/ha was
applied and this was the highest. Except for the number of nodules recorded for pigeonpea (19)
at a rate of 200 kg P/ha which was lower than the number of nodules formed on soybean (40)
at the same rate of phosphorus application, nodule numbers recorded for pigeonpea were higher
than those for soybean at the other rates of phosphorus applied.
In the Bekwai soil, the application of 40 kg P/ha and 80 kg P/ha gave no significant increases
in nodule numbers for pigeonpea over the control (Fig. 1). Nodule numbers recorded at rates
160 and 200 kg P/ha were significantly (P < 0.05) higher than that for the control (equivalent
to about 5-fold and 8-fold increases at 160 and 200 kg P/ha, respectively). None of the rates of
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phosphorus applied on the other hand was able to reverse the inability of soybean to form
Number of nodules per plant
nodules in the Bekwai soil (Fig. 1).
120
Fertilizer rates
100
P0
80
P40
60
P80
40
P120
20
P160
0
Pigeonpea
Soybean
Pigeonpea
Adenta
Soybean
P200
Bekwai
Rate of Phosphorus applied (kg P/ha)
Fig. 1. Effect of phosphorus fertilizer application on the number of nodules formed on
soybean and pigeonpea grown in the Adenta and Bekwai series
4.3.2 Effect of phosphorus fertilizer application on dry weight of nodules formed on
soybean and pigeonpea.
In the Adenta soil the dry weights of nodules formed on pigeonpea and soybean in the control
treatments were, 63.30 mg and 3.30 mg, respectively. When 40 kg P/ha was applied to the
Adenta soil, no increases over the controls in the nodule dry weights were recorded for
pigeonpea and soybean. Phosphorus application up to120 kg P/ ha in the Adenta soil resulted
in no significant (P > 0.05) increase in the dry weights of nodules formed on pigeonpea (Fig.
2). Above 120 kg P/ha, any increase in the rate of phosphorus applied resulted in decreases in
the dry weight of nodules formed (Fig. 2). Pigeonpea receiving 200 kg P/ha recorded a 52.6 %
decrease in nodule dry weight compared to the control.
Nodulation in soybean was increased to 6.70 mg and 10.00 mg when 80 kg P/ha and 120 kg
P/ha, respectively, were applied. Increased application to 160 kg P/ha and 200 kg P/ha resulted
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in 40.00 mg and 80.00 mg nodule dry weights, respectively, which translate into 11-fold and
23-fold increases (significant at P < 0.05), respectively. The highest dry weight of nodules was
recorded at 200 kg P/ha.
Application of phosphorus to pigeonpea in the Bekwai soil resulted in a significant increase in
nodule dry weight from 10. 00 mg at the 0 kg P/ha rate to 116.7 mg at the 200 kg P/ha rate. No
significant increases in nodule dry weights were recorded among treatments 0, 40, 80, 120 and
160 kg P/ha. The increase recorded when 200 kg P/ha was applied translates into 10-fold that
Dry weight of nodules (mg/plant)
of the control and was the highest.
120.0
Fertilizer rates
100.0
P0
80.0
P40
60.0
P80
40.0
20.0
P120
0.0
P160
Pigeonpea
Soybean
Pigeonpea
Adenta
Soybean
P200
Bekwai
Rate of Phosphorus applied (kg P/ha)
Fig. 2. Effect of phosphorus fertilizer application on the dry weight (g) of nodules formed
on soybean and pigeonpea.
4.3.3 Nitrogen fertilizer application and nodulation of soybean and pigeonpea
In contrast to pigeonpea, with or without applied N, soybean did not nodulate in the Bekwai
soil (Fig. 3). The number of nodules recorded for pigeonpea and soybean in the control
treatments (when no nitrogen was applied) were 6 and 0, respectively. For both legumes,
nitrogen fertilizer application was detrimental to nodule formation in both soils. In the Adenta
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soil the highest numbers of nodules were formed on both legumes at the 0 kg N/ha rate (Fig.
3). The numbers of nodules recorded for pigeonpea and soybean in the control treatments were,
65 and 6, respectively. When 40 kg N/ha was applied to the Adenta soil, the number of nodules
recorded for pigeonpea was 48 and this was 26.2 % lower than that recorded for the control.
Further decreases in nodule numbers were recorded on pigeonpea upon increasing the rate of
nitrogen applied up to 200 kg N/ha (Fig. 3). However, nodulation among the treatments
receiving 120, 160 and 200 kg N/ha was not significant (P > 0.05). In the case of soybean,
application of 40 kg N/ha decreased the number of nodules formed in the Adenta soil by 33.3
% and the application of 200 kg N/ha decreased the number of nodules formed from six (6) in
the control to zero (0), indicating a complete inhibition of nodulation at the 200 kg N/ha rate.
The number of nodules recorded for pigeonpea were significantly higher than those recorded
for soybean at all the rates of nitrogen fertilizer applied with the mean number of nodules
recorded for pigeonpea being significantly higher than that recorded for soybean.
Number of nodules per plant
80
Fertilizer rates
N0
60
N40
N80
40
N120
20
N160
N200
0
Pigeonpea
Soybean
Pigeonpea
Adenta
Soybean
Bekwai
Rate of Nitrogen applied (kg N/ha)
Fig. 3. Effect of nitrogen fertilizer application on the number of nodules formed on
soybean and pigeonpea grown in the Adenta and Bekwai series.
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4.3.4 Effect of nitrogen fertilizer application on the dry weight of nodules formed on
soybean and pigeonpea.
In the control treatments, the dry weights of nodules formed were, 63.30 mg and 3.30 mg for
pigeonpea and soybean, respectively in the Adenta soil and 10.00 mg for pigeonpea in the
Bekwai soil. In the Adenta soil, application of nitrogen at 40 kg N/ha resulted in 26.2 %
decrease in the dry weight of nodules formed on pigeonpea. The dry weights of nodules
recorded at rates 120 kg N/ha, 160 kg N/ha and 200 kg N/ha were all significantly lower (P <
0.05) than that for the control (Fig. 4). When 40 kg N/ha was applied to the Adenta soil, the
measuring scale could not weigh the dry weight of soybean nodules obtained.
In the Bekwai soil, application of 40 kg N/ha decreased the dry weight of nodules formed on
pigeonpea to 3.00 mg. The measuring scale could not weigh the dry weight of pigeonpea
Nodule dry weight (mg/plant)
nodules formed at 80 Kg N/ha. No nodules were formed beyond 80 kg N/ha.
Fertilizer rates
80.0
N0
60.0
N40
N80
40.0
N120
20.0
N160
N200
0.0
Pigeonpea
Soybean
Pigeonpea
Adenta
Soybean
Bekwai
Rate of Nitrogen applied (kg N/ha)
Fig. 4. Effect of nitrogen fertilizer application on dry weight (g) of nodules formed on
soybean and pigeonpea grown in the Adenta and Bekwai series.
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4.3.5 Combined application of phosphorus and nitrogen fertilizers on nodulation of
soybean and pigeonpea.
In the Adenta soil, with no N and P application, numbers of nodules formed on pigeonpea and
soybean were 65 and 6, respectively. With 40 kg P/ ha applied there was no effect on the number
of nodules formed on soybean whereas the nodules formed on pigeonpea were increased to 72.
Nodulation was enhanced (26 nodules) when 100 kg N/ ha was combined with 120 kg P/ ha. A
combination of 160 kg P/ha and 100 kg N/ha increased the nodule number over the control. The
combined application of 100 kg N/ ha and 200 kg P/ha, however, decreased nodulation
compared to the control (Fig. 5). Application of combined 100 kg N/ ha and 40 kg P/ ha revived
nodulation (3 nodules) in soybean. When 80 kg P/ha was applied together with 100 kg N/ha,
the number of nodules formed on soybean in the Adenta soil was increased slightly to seven (7)
and this was similar to the control. Soybean in the Adenta soil receiving P at the rates of 120
kg P/ha and 160 kg P/ha each produced more than 4 times the number of nodules in the control
treatment with the value for the 120 kg P/ha rate being the highest (Fig. 5). Increasing the P rate
to 200 kg P/ha reduced the number of nodules compared to the control treatment (N0P0 kg/ha)
but not significantly.
In the Bekwai soil, six nodules were recorded for pigeonpea in the control treatment.
Application of P at rates 40 kg P/ha and 80 kg P/ha in combination with the inhibitory rate of
100 kg N/ha resulted in the formation of 1 nodule in each case. Nodulation was restored to the
level of the control (Fig. 5) when 100 kg N/ha was combined with 120 kg P/ha. Further increase
in the P rates beyond 120 kg P/ha up to 200 kg P/ha in combination with 100 kg N/ ha increased
the number of nodules to 21 and 32 for the 160 kg P/ ha and 200 kg P/ha rates, respectively.
The increases observed translate into 3-folds and 5-folds for the 160 kg P/ ha and 200 kg P/ha
rates, respectively, compared to the control. Soybean on the other hand did not nodulate at all
in all the treatments.
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Number of nodules per plant
80
70
Fertilizer rates
N0P0
60
N0P40
50
N100P40
40
N100P80
30
N100P120
20
N100P160
10
N100P200
0
Pigeonpea
Soybean
Pigeonpea
Adenta
Soybean
Bekwai
Fertilizer rates applied (kg/ha)
Fig. 5. The effect of combined application of phosphorus and nitrogen fertilizers on the
number of nodules formed on soybean and pigeonpea grown in the Adenta and Bekwai
series.
4.3.6 The combined application of nitrogen and phosphorus fertilizers on the dry weight
of nodules formed on soybean and pigeonpea.
In the Adenta soil, with no N and P applied, dry weight of nodules formed on pigeonpea and
soybean were 63.30 mg and 3.30 mg, respectively. Combined application of 100 kg N/ha and
40 kg P/ha did not give any significant increase in dry weight of nodules above the control in
both legumes. Nodulation in pigeonpea was, however, boosted when 100 kg N/ ha was
combined with 200 kg P/ ha resulting in the formation of nodules weighing 60.00 mg. With the
combined application of 100 kg N/ ha and 80 kg P/ha, the dry weight of nodules formed on
soybean increased greatly to 13.30 mg. The highest dry weight of nodules formed on soybean
(73.30 mg) was recorded when 100 kg N/ ha was applied in combination with 120 kg P/ ha.
The dry weight of nodules decreased with combined application of 100 kg N/ ha and 160 kg P/
ha although the value recorded (60 mg) was still high compared to the control (3.30 mg). The
dry weight of nodules formed on soybean was further decreased when 100 kg N/ha was applied
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in combination with 200 kg P/ha and the value recorded was same as that for the control (Fig.
6).
In the Bekwai soil, with no N and P application, dry weight of nodules formed on pigeonpea
was 10.00 mg. Nodulation was revived when 100 kg N/ ha was combined with 120 kg P/ ha
resulting in the formation of nodules weighing 33.30 mg. Increasing the rate of phosphorus
applied in the combined fertilizer treatment to 160 kg P/ha resulted in a dry weight of 166.7 mg
for the nodules formed and this was the highest. The increases observed at rates 120 kg P/ha
and 160 kg P/ha applied were significant (P < 0.05) and translate into 9-fold and 50-fold,
respectively. A decrease in nodule dry weight relative to the 160 kg P/ha rate was observed
when phosphorus was applied at 200 kg P/ha. Thus, treatments receiving 120, 160 and 200 kg
Nodule dry weight (mg/plant)
P/ha reversed the N inhibition effect on the dry weight of nodules formed.
200.0
Fertilizer rates
N0P0
160.0
N0P40
120.0
N100P40
N100P80
80.0
N100P120
40.0
N100P160
N100P200
0.0
Pigeonpea
Soybean
Pigeonpea
Adenta
Soybean
Bekwai
Fertilizer rates applied (kg/ha)
Fig. 6. The combined application of nitrogen and phosphorus fertilizers on dry weight (g)
of nodules formed on soybean and pigeonpea.
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4.3.7 Effect of phosphorus fertilizer application on shoot dry weight production by
soybean and pigeonpea.
The shoot dry weight values for pigeonpea and soybean in the phosphorus control treatments
in the Adenta soil were 2.31 g and 5.99 g, respectively (Fig. 7). Application of 40 kg P/ha
resulted in about 90.9 % and 3.3 % increases in shoot dry weight for pigeonpea and soybean,
respectively. When the rate of phosphorus applied was increased to 80 kg/ha, pigeonpea
recorded an even higher (138 %) shoot dry weight over the control than soybean (5 %).
Pigeonpea recorded the highest response at rate 160 kg P/ha which was more than 2-folds
compared to the control. Soybean on the other hand recorded the highest response at rate 200
kg P/ha though this was very low (0.3 fold) when compared to that for pigeonpea. Pigeonpea
recorded a decrease in shoot dry weight when 200 kg P/ha was applied. Soybean recorded,
higher shoot dry weights than pigeonpea at all levels of phosphorus applications.
The shoot dry weights of pigeonpea and soybean grown in unfertilized Bekwai soil were 2.37
g and 1.77 g, respectively. Application of 40 kg P/ha resulted in about 22 % and 183 % increases
in shoot dry weights of pigeonpea and soybean, respectively. Whereas an increase in the rate
of phosphorus fertilizer to 80 kg P/ha gave a 0.7-fold increase in shoot dry weight over the
control for pigeonpea, the increase observed for soybean receiving the same level of phosphorus
application was about 2-folds more than the control. When the P rate was further increased from
80 kg P/ha up to 200 kg P/ha, both legumes gave significant increases in shoot dry weight and
both legumes recorded highest weight of dried shoots at 200 kg P/ha.
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Shoot dry weight (g/plant)
10.00
Fertilizer rates
P0
8.00
P40
6.00
P80
4.00
P120
2.00
P160
0.00
Pigeonpea
Soybean
Pigeonpea
Adenta
Soybean
P200
Bekwai
Rate of Phosphorus applied (kg P/ha)
Fig. 7. Effect of phosphorus fertilizer application on shoot dry weight (g) of soybean and
pigeonpea grown in the Adenta and Bekwai soils.
4.3.8 Effect of nitrogen fertilizer application on shoot dry weight of soybean and
pigeonpea.
Except for soybean growing in the Bekwai soil which recorded varying responses with nitrogen
application, the control (0 kg N/ha) in all cases recorded the lowest dry weight of shoots (Fig.
8). In the Adenta soil, without N fertilizer, the shoot dry weights were 2.31 g and 5.99 g for
pigeonpea and soybean respectively, and when nitrogen was applied at the rate of 40 kg N/ha,
64 % and 15 % increases in the dry weight of shoots were obtained for pigeonpea and soybean,
respectively. Doubling the nitrogen rate at 80 kg N/ha increased the weight of dried shoots to
5.61 g and 9.21 g for pigeonpea and soybean, respectively. The increases in shoot dry weight
were 142 % and 54 % more than those for the controls for pigeonpea and soybean, respectively.
Increasing the nitrogen rates to 120, 160 and 200 kg N/ha resulted in lower shoot dry weights
than the values recorded for the treatments at the 80 kg N/ha. There was, however, no significant
difference between shoot dry weights recorded for pigeonpea at rates of 80 kg N/ha and 120 kg
N/ha. The shoot dry weights for soybean were higher than those for pigeonpea at all levels of
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nitrogen application in the Adenta soil. In the Bekwai soil the shoot dry weight values recorded
for pigeonpea and soybean in the nitrogen control treatments were 2.37 g and 1.77 g,
respectively (Fig. 8). Application of 40 kg N/ha resulted in only 4 % and 7 % increases in shoot
dry weight for pigeonpea and soybean, respectively. Whereas an increase in the rate of nitrogen
fertilizer to 80 kg N/ha gave a 40 % increase in shoot dry weight of pigeonpea over the control,
a negative response was recorded for soybean indicating a decrease. When the rate was further
increased to 160 kg N/ha soybean still recorded decreases in shoot dry weights but with a
dramatic increase of 46 % over the control when 200 kg N/ha was applied. Both legumes
Shoot dry weight (g/plant)
recorded highest shoot dry weights in the treatments receiving 200 kg N/ha.
10.00
Fertilizer rates
8.00
N0
6.00
N40
4.00
N80
N120
2.00
N160
0.00
Pigeonpea
Soybean
Pigeonpea
Adenta
Soybean
N200
Bekwai
Rate of Nitrogen applied (kg N/ha)
Fig. 8. Effect of nitrogen fertilizer application on shoot dry weight (g) of soybean and
pigeonpea grown in the Adenta and Bekwai series.
4.3.9 The effect of the combined application phosphorus and nitrogen fertilizers on shoot
dry weight of soybean and pigeonpea.
In the Adenta soil with no N or P applied shoot dry weights were 5.99 g and 2.31 g for soybean
and pigeonpea, respectively. When only phosphorus was applied, at a rate of 40 kg P/ha, the
shoot dry weights for soybean and pigeonpea, increased to 6.19 g and 4.41 g, respectively.
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These values, although higher than those for the controls in the separate applications of the
fertilizers, were further increased when either N or P rates were increased. (Fig. 7 and Fig. 8).
Addition of 100 kg N/ha to the 40 kg P/ha led to a 25.8 % increase in shoot dry weight of
soybean. When the rate of phosphorus was increased to 80 kg P/ha while maintaining the rate
of nitrogen at 100 kg N/ha, increases in shoot dry weights were recorded for both pigeonpea
and soybean (Fig. 9). The increases recorded for both pigeonpea and soybean were comparable
to the highest shoot dry weight recorded in the treatments with separate fertilizer applications
(Tables 3 and 4). Soybean recorded the highest dry weight of shoot when 80 kg P/ha was applied
together with 100 kg N/ha. When 160 kg P/ha was combined with 100 kg N/ha in the Adenta
soil, the dry weight of soybean shoots increased but not significantly higher than the shoot dry
weight recorded when 80 kg P/ ha was combined with 100 kg N/ ha. Pigeonpea recorded the
highest shoot dry weight when 160 kg P/ha was applied. Application of 200 kg P/ha combined
with 100 kg N/ha decreased the shoot dry weight (Fig. 9). Soybean recorded significant
decreases when phosphorus was applied above 80 kg P/ha. In the Bekwai soil the control
without N or P produced 1.77 g and 2.37 g of dried shoot for soybean and pigeonpea,
respectively. Application of 40 kg P/ha resulted in significant increases to 2.89 g and 5.01 g of
shoot dry weight for pigeonpea and soybean, respectively. Application of 100 kg N/ha together
with 40 kg P/ha gave 3.07 g and 4.86 g shoot dry weight for pigeonpea and soybean,
respectively. The highest shoot dry weight produced by soybean (7.17g) was recorded when
100 kg N/ha was applied in combination with 200 kg P/ha. There were progressive increases in
shoot dry weight of pigeonpea up to P120 kg/ha (5.37 g), after which a decrease occurred (Fig.
9).
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Shoot dry weight (g/plant)
.
8.00
Fertilizer rates
N0P0
6.00
N0P40
4.00
N100P40
2.00
N100P80
10.00
N100P120
0.00
Pigeonpea
Soybean
Pigeonpea
Adenta
Soybean
Bekwai
N100P160
N100P200
Fertilizer rates applied (kg/ha)
Fig. 9. Effect of combined application of phosphorus and nitrogen on shoot dry weight (g)
of soybean and pigeonpea.
4.4 Effect of phosphorus application on nodulation and nitrogen fixation in soybean in
Adenta series
Number of nodules formed
Nodule formation was enhanced by P application (Table 3). Two nodules were formed on
soybean in the treatment receiving no phosphorus application and this was the lowest.
Phosphorus application at 40 kg P/ha resulted in increased number of nodules equivalent to
about 10 times the number of nodules recorded in the treatment receiving no phosphorus.
Increasing the rate of phosphorus applied to 80 kg P/ha resulted in the formation of 40 nodules
which was 20-folds the number of nodules recorded for the control indicating that doubling the
rate of phosphorus application gave twice as much the number of nodules formed. A further
increase in the rate of phosphorus applied to 120 kg P/ha resulted in the formation of 44 nodules
on soybean which also gave 22-folds the number of nodules formed on the control plants.
However, the increase in nodule number was not significantly different from the nodules
produced by the application of 40 kg P/ ha.
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Dry weight of nodules formed
The results for the dry weights of nodules revealed a trend similar to that observed for nodule
numbers. The lowest dry weight of nodules (2.99 mg) was recorded in the control (Table 3).
Application of phosphorus resulted in increased dry weight of nodules up to the 120 kg P/ ha
rate (Table 3). The highest dry weight of nodules recorded was 65.78 mg, was obtained when
120 kg P/ha was applied. Significant increases in dry weight of nodules over the control were
recorded at all levels of P applied (Table 3). The dry weight produced per nodule was found not
to respond to phosphorus application (Table 3).
Total nitrogen in shoot
The values for total nitrogen in shoot was found to increase with P application, and ranged from
the lowest (65.73 mg) in the control treatment to the highest (93.86 mg) when 120 kg P/ha was
applied. Application of P above 40 kg P/ha gave significant (P < 0.05) increases over the control
(Table 3) and also over the preceding rates.
Percent nitrogen derived from fixation
When no P was applied, 23.1 % of the total nitrogen in shoot was derived from atmospheric N2
fixation. The percentage of N derived from the atmosphere (% Ndfa) increased with increased
P application with the 120 kg P/ ha rate giving the highest (54.7 %). However, the most efficient
response in % Ndfa occurred when 40 kg P/ ha was applied increasing % Ndfa from 23.1 % in
the control to 44.80 %, almost double.
Total nitrogen derived from fixation
The total nitrogen derived from fixation for the control was 15. 6 mg and this was the lowest
recorded. Application of phosphorus at a rate of 40 kg P/ha increased the amount of nitrogen
fixed to 32.27 mg, which was more than two times that of the control. With a further increase
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in P application to 80 kg P/ha increase in total nitrogen fixed was not significant. The highest
and significant increase in total nitrogen fixed (51.50 mg) occurred when 120 kg P/ha was
applied (Table 3).
Nitrogen fixation efficiency (N2-fixed/mg nodule)
The total nitrogen fixed per mg nodule decreased with P application (Table 3). With no P
applied, each mg dry weight of nodule fixed 5.21 mg N in soybean and this was the highest for
all treatments. The application of P at a rate of 40 kg P/ha resulted in a substantial (23.3 %)
decrease in N2 fixed. Further increases in P application gave non-significant (P > 0.05)
decreases in N2 fixed and the values were 1.11 mg, 0.79 mg and 0.78 mg for the rates 80 kg
P/ha, 120 kg P/ha and 160 kg P/ha, respectively.
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Table 3. Effect of phosphorus application on nodulation and nitrogen fixation in soybean grown in Adenta soil.
Phosphorus (kg/ha)
NN
NDW (mg)
DW/N (mg) SDWT (g)
TNS (mg)
% Ndfa
TNF (mg)
TNF (mg)/ mg NDW
P0
2c
2.99d
1.50a
1.0d
67.53c
23.1c
15.57c
5.21a
P40
19b
28.99c
1.53a
2.5c
71.67c
44.8b
32.27b
1.11b
P80
40a
51.17b
1.28a
4.4b
84.15b
47.8b
40.41b
0.79b
P120
44a
65.78a
1.50a
5.3a
93.86a
54.7a
51.50a
0.78b
Mean (SE)
26 (± 9.77)
37.23 (± 13.69) 1.45 (± 0.06) 3.3 (± 0.96)
79.3 (± 6.00) 42.6 (± 6.82) 34.94 (± 7.56) 1.97 (± 1.08)
LSD (0.05)
9.9
8.12
0.76
0.3
9.59
5.1
8.60
0.54
CV (%)
24.8
14.2
3.09
21.6
7.9
7.8
16.0
17.9
NB: Means having the same letters under the same column are not significantly different from one another.
SDW: Shoot dry weight:
NDW: Nodule dry weight
% NS: Percent nitrogen in shoot.
NN: Nodule number DW/N: Dry weight per nodule
TNS: Total nitrogen in shoot
% Ndfa: Percent nitrogen derived from atmosphere (fixation)
TNF: Total nitrogen fixed.
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4.4.1 Effect of phosphorus application on shoot dry weight of soybean grown in the Adenta
and Nzima soils.
With no phosphorus application, shoot dry weight of soybean was higher in the Adenta series
(2.16 g) than in the Nzima series (1.00 g). Application of 40 kg P/ha more than doubled the dry
weight of shoots in both soils (Fig. 10). The dry weight of shoot recorded for the treatment
receiving 40 kg P/ha in the Adenta soil was significantly higher than that in the Nzima soil
(Fig.10). When the fertilizer rate was increased to 80 kg P/ha, shoot dry weight produced by
soybean in the Nzima soil was about hundred percent more than that for the preceding rate (40
kg P/ha). The case was different in the Adenta soil where the corresponding increase in shoot dry
weight recorded was less than 10 percent. A further increase in the fertilizer rate resulted in an
increase in the dry weight of shoots from both soils. The higher responses observed in the Nzima
soil with P application resulted in the shoot dry weight of soybean becoming higher in the Nzima
than in the Adenta soil at the 120 kg P/ha rate (Fig 10).
Shoot dry weight (g/plant)
6
5
4
3
2
1
0
Adenta
Nzima
P0
2.16
1
P40
4.08
2.47
P80
4.4
4.44
P120
4.69
5.25
Fertilizer rates applied (kg P/ha)
Fig. 10. Effect of phosphorus application on shoot dry weight production by soybean grown
in the Adenta and Nzima soils.
Lsd (5 %): Phospphorus = 0.34, Soil = 0.24, Soil*Phosphorus interaction = 0.48
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4.5 Genetic diversity of indigenous soybean, pigeonpea and cowpea rhizobial strains in
Adenta, Bekwai and Nzima soils.
The diversity of Bradyrhizobium isolates that nodulated soybean and pigeonpea in the Adenta,
Bekwai and Nzima soils was evaluated with or without phosphorus fertilization. The inclusion
of cowpea was to examine how related the Bradyrhizobium isolates that nodulated soybean and
pigeonpea were to those that nodulated cowpea. Neither of the locations from which the soils
were sampled had a known history of inoculation with rhizobia. As such the isolates trapped by
these legumes were assumed to be indigenous to the soils.
4.5.1 Electrophoresed gel images of the PCR amplified products by the different Primers.
4.5.1.1 PCR amplification of the 16S rDNA region of the isolates
The amplification profiles for the 16S PCR revealed a 1500 bp DNA fragment (Fig. 11) that was
consistent for all the Bradyrhizobium isolates. A non-variable 600 bp fragment that persisted in
the majority of isolates was also observed from this PCR. From Fig. 11, this fragment was
amplified for pigeonpea isolates PBF-3, PBF-13, PBF-14, PBF-15, PBF-16, PBF-17, PBF-18
and PBF-19, PNF-7 and PNF-8.
V
Fig. 11. Sample of PCR amplification of Bradyrhizobium DNA using primer targeting the
16S conserved region.
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The letter P stands for pigeonpea. The letters B and N stand for Bekwai and Nzima soils,
respectively. The letters M and V represent ladder lane and negative control, respectively. The
letter F stands for P fertilised treatments.
4.5.1.2 PCR amplification of the 23S rDNA region of the isolates
The 23S PCR amplifications produced a DNA fragment of size 2900 bp (Fig. 12) which was
consistent for all the Bradyrhizobium isolates including the reference strain USDA 110. No
additional fragment was observed from this PCR amplification. Some amplicons recorded no
bands (Fig. 12) because of technical problems. As such PCR amplification of the DNAs
corresponding to these regions was repeated and the 2900 bp DNA fragment was successfully
amplified for the isolates.
Fig. 12. Sample of PCR amplification of Bradyrhizobium DNA using primer targeting the
23S conserved region.
The letters C and P stand for cowpea and pigeonpea, respectively, while A, B and N stand for
Adenta, Bekwai and Nzima soils, respectively, and M represents ladder lane. The letters F and
U stand for P fertilised and unfertilised treatments, respectively.
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4.5.1.3 PCR amplification of the ITS region of the isolates
From Fig. 13, the ITS primer targeted PCR for the bradyrhizobial isolates was able to amplify
the ITS conserved region for all the DNA samples and discriminated between isolates by
producing fragments with band size ranging from 300 bp to 700 bp.
Fig. 13 Sample of PCR amplification of Bradyrhizobium DNA using primer targeting the
16S-23S ITS conserved region.
The letter C stands for cowpea, A and N represent Adenta and Nzima soils, respectively and M
represents ladder lane. The letters F and U stand for P fertilised and unfertilised treatments,
respectively.
4.5.1.4. PCR analysis of the total genomic DNA of the isolates using primer RPO1
Figure 14 shows RPO1 PCR amplified DNA from the isolates. This produced fragments with
band sizes ranging from as short as 117 bp to as long as 1800 bp. Figure 14 further showed the
discriminating ability of the RPO1 primer as it differentiated among the isolates. The DNA
pattern of isolate SNF-2 was similar to the banding patterns of the soybean isolates from the
Adenta soil with P-fertilization and different from the other soybean isolate SNF-1 from Nzima
soil with P-fertilization. The banding patterns of the cowpea isolates CNF-12 and CNF-16 were
similar and different from those of the other cowpea isolates CNF-1, 2, 17 and CNF-18 (Fig. 14).
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Amplification of a 600 bp DNA fragment was observed from this PCR and was consistent for
the majority of isolates (Fig. 14). No two isolates produced the same banding patterns from this
PCR to infer 100 % similarity.
Fig. 14. Sample of PCR amplification of Bradyrhizobium DNA using primer RPO1.
The letters S and C represent soybean and cowpea, respectively, N and A represent Nzima and
Adenta soils, respectively and M represents ladder lane. The letter F stands for P fertilised
treatments.
4.5.1.5 PCR analysis of the total genomic DNA of the isolates using primer RPO4
From Fig. 15, PCR amplification of DNA from the isolates using the arbitrary oligonucleotide
primer RPO4 produced fragments with band sizes ranging from as short as 157 bp to as long as
3000 bp. The banding patterns of the DNA fragments obtained by this PCR could also
differentiate among the isolates and the reference strain as well and established groups among
the isolates. From Fig. 15 the PCR differentiated between isolates that nodulated cowpea in the
Nzima soil with P and those that nodulated cowpea in the Adenta soil with or without P and
further differentiated within isolates from the Adenta soil. As shown in Fig. 15, cowpea isolates
from the Adenta soil with P, had two groups (five isolates in each group) with isolates in each
group having similar banding patterns
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Fig. 15. Sample of PCR amplification of Bradyrhizobium DNA using primer RPO4.
The letter C represents cowpea, A stands for Adenta soil and M represents ladder lane. The letters
F and U stand for P fertilised and unfertilised treatments, respectively
4.5.2 Clustering on the basis of PCR amplification with RPO1 and RPO4.
This section presents the results of hierarchical clustering of the data generated from the PCR gel
images using the Unweighted Paired Group Arithmetic Method (UPGMA). Indices of diversity
were calculated based on clusters that were formed at 80 % similarity.
4.5.2.1 Phylogenetic relationships among cowpea Bradyrhizobium isolates in Adenta soil as
determined by combined matrices for RPO1 and RPO4 PCR.
All the 21 isolates (eleven from unfertilised treatments and ten from fertilised treatments) that
nodulated cowpea in the Adenta soil were 66 % similar (Fig. 16). Above the mean similarity of
66 %, two main clusters A and B were observed. One isolate, CAU-11 being the most similar
(72 %) to the reference strain, USDA110 grouped together with the reference strain in cluster A.
The remaining 20 cowpea isolates were differentiated into sub-clusters under cluster B above a
mean 74 % similarity level. At 80 % similarity, the isolates within cluster A were differentiated
into two sub-clusters, I and II. The isolates within cluster B were further differentiated into three
sub-clusters which were designated I, II and III at the same 80 % similarity level. About 33.3 %
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of the cowpea isolates were grouped into sub-cluster I with a mean similarity of 84 %. The
isolates that grouped under sub-cluster I were those that nodulated cowpea in either `P-fertilized
or P-unfertilized Adenta soil (Fig. 16). The isolates within sub-clusters II and III were 88 % and
82 % similar, respectively. All the five isolates within sub-cluster II (CAF-6-10) were from
treatments receiving P. Sub-cluster III on the other hand contained eight isolates all of which
were from treatments without P. The isolates in sub-cluster III were placed farther apart from the
other cowpea isolates (CAU-11 and CAU-9, 10) from Adenta soil without P. The isolates CAU11 and CAU-9, 10 were also clustered farther apart from each other (Fig. 16). The following
groups of isolates; CAU-2-3, CAU-6-7, CAF-6-9 and CAF-1, 4 were similar, scoring 95 %
similarity. The most similar isolates were CAF-6-8 with a similarity of 96 %. All the isolates
were dissimilar above 96 % similarity level. The Shannon-Weaver diversity and Pielou Evenness
indices were 1.22 and 0.88, respectively for the clustering among the 21cowpea isolates.
CAU-1
CAU-2
CAU-3
III
CAU-4
CAU-8
CAU-6
CAU-7
CAU-5
CAF-10
B
II
CAF-6
CAF-7
CAF-8
CAF-9
CAU-10
CAF-3
I
CAU-9
CAF-1
CAF-4
CAF-2
I II
A
0.65
CAF-5
0.73
0.80
CAU-11
US DA110
0.88
0.96
Coefficient
Fig. 16. Dendogram indicating relationships among cowpea isolates in Adenta soil based on
combined RPO1 and RPO4 PCRs
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4.5.2.2 Phylogenetic relationships among cowpea Bradyrhizobium isolates in Bekwai soil as
determined by combined matrices from RPO1 and RPO4 PCR.
All the 12 cowpea isolates in the Bekwai soil were from treatments receiving P. At a similarity
of 61 %, all the isolates together with the reference strain were similar (Fig. 17). Beyond the
mean similarity of 61 %, two distinct clusters, A and B were formed. The reference strain was
separated into Cluster A while all the 12 cowpea isolates were grouped under Cluster B at 69 %
similarity. At 80 % similarity, seven sub-clusters were formed under cluster B (Fig. 17). The
isolates CBF-6, CBF-12, CBF-5, CBF-3 and CBF-11 were separately clustered into BI, BII, BIV,
BV and BVII, respectively. Sub-clusters BIII and BVI contained three isolates each equivalent
to 25 % of the total isolates. The isolates within sub-cluster BIII were 80 % similar whereas those
in BVI were 83 % similar. The isolates CBF-7 and CBF-8 were the most similar at 93 % level
above which all the isolates were dissimilar. The Shannon-Weaver diversity and the Pielou
Evenness indices were calculated as 1.74 and 0.90, respectively for the clusters formed in Fig.
17.
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VII
.
CBF-11
VI
CBF-1
CBF-4
V
CBF-2
IV
CBF-3
CBF-5
B
III
CBF-10
CBF-7
CBF-8
II
CBF-9
CBF-12
A
I
CBF-6
0.60
USDA110
0.68
0.77
Coefficient
0.85
0.93
Fig. 17. Dendogram indicating relationships among cowpea isolates in Bekwai soil based on
combined RPO1 and RPO4 PCRs
4.5.2.3 Phylogenetic relationships among cowpea Bradyrhizobium isolates in Nzima soil as
determined by combined matrices from RPO1 and RPO4 PCR.
All the 19 isolates were from nodules on cowpea grown in Nzima soil with P fertilization and
were similar at 67 % level (Fig. 18). At 64 % level, all the cowpea isolates were similar to the
reference. Above the mean similarity of 64 %, two main clusters A and B were formed. Cluster
A contained the reference strain whereas cluster B contained the 19 cowpea isolates that were
further clustered into two distinct groups above a mean similarity of 67 %. Nine out of the 19
isolates were differentiated from the other cowpea isolates into one group at 70 % similarity level
with the remaining isolates forming another group with a mean similarity of 72 %. At 80 %
similarity level, the cowpea isolates were grouped into ten new sub-clusters, I-X. Isolates CNF86
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15 and CNF-16 were the most similar at 98 % level above which all the isolates were dissimilar
The Shannon-Weaver diversity and the Pielou evenness indices for this dendogram were 2.11
X
and 0.91, respectively.
CNF-9
CNF-16
CNF-10
CNF-11
CNF-4
I
VI I
VII
I
X
CNF-15
I
V
CNF-5
CNF-6
V
CNF-7
CNF-8
B
CNF-18
V
I
CNF-17
CNF-1
CNF-2
III
CNF-12
CNF-13
II
CNF-19
A
CNF-3
I
CNF-14
0.62
USDA110
0.71
0.80
Coefficient
0.89
0.98
Fig. 18. Dendogram indicating relationships among cowpea isolates in Nzima soil based on
combined RPO1 and RPO4 PCRs
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4.5.2.4 Phylogenetic relationships among cowpea Bradyrhizobium isolates from all the soils
as determined by combined matrices from RPO1 and RPO4 PCR.
From Fig. 19, all the 52 cowpea isolates from the study were 65 % similar to the reference strain.
Above the mean similarity of 65 %, the isolates were grouped into two main clusters, A and B.
Isolate CAU-11 was clustered together with the reference strain, USDA110 in A at 70 %
similarity. The remaining 51 cowpea isolates from this PCR were clustered into B at about 67 %
similarity level. The isolates in cluster B were further grouped into BI and BII at about 73 %
similarity. Sub-cluster BI contained only isolates from the Nzima soil which were 76 % similar.
Cluster BII contained isolates that nodulated cowpea grown in the three soils studied. At about
73 % similarity, the isolates in cluster BII were grouped into five sub-clusters a, b, c, d and e.
Sub-cluster IIa contained four Isolates that were differentiated into separate clusters at 80 %
similarity (Fig. 19). Sub-clusters IIb and IIc contained only isolates that nodulated cowpea in the
Bekwai soil. Sub-cluster IId contained two cowpea isolates from the Nzima soil with P grouped
together with two cowpea isolates from the Adenta soils without P and five other isolates from
the Adenta soil with P application. Cluster IIe contained isolates obtained from all the soils used
with or without P application at 73 % similarity. Isolates CNF-15 and CNF-16 were the most
similar at 98 % similarity above which all the isolates were dissimilar The sub-clusters formed
at 80 % similarity are presented in Table 4 for simplicity The Shannon-Weaver diversity and the
Pielou evenness indices were 2.75 and 0.90, respectively.
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A
I
a
b
B
c
d
II
e
CAU-1
CAU-2
CAU-3
CAU-4
CAU-8
CAU-6
CAU-7
CNF-9
CAU-5
CNF-10
CNF-11
CNF-5
CNF-6
CAF-10
CAF-6
CAF-7
CAF-8
CAF-9
CNF-19
CBF-5
CNF-15
CNF-16
CAU-10
CAF-3
CAU-9
CAF-1
CAF-4
CAF-2
CAF-5
CNF-7
CNF-8
CBF-11
CBF-1
CBF-4
CBF-2
CBF-3
CBF-10
CBF-7
CBF-8
CBF-9
CBF-12
CNF-4
CBF-6
CNF-3
CNF-18
CNF-17
CNF-1
CNF-2
CNF-12
CNF-13
CNF-14
CAU-11
USDA110
0.64
0.72
0.81
Coefficient
0.90
0.98
Fig. 19. Dendogram indicating relationships among Cowpea isolates in Adenta, Bekwai and
Nzima soil based on combined RPO1 and RPO4 PCRs
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Table 4. Clustering of isolates obtained from cowpea nodules from all the soils at 80 %
similarity
Similarity level
66 %
67 % 70 % 80 %
Cluster
Sub-cluster
Isolates
A
B
I
a
II
a
1
2
1
2
3
4
1
2
1
2
3
1
2
1
2
3
4
5
6
7
b
c
d
e
CAU-11
USDA110
CNF-12 to 14
CNF-1,2,17,18
CNF-3
CBF-6
CNF-4
CBF-12
CBF-7 to 9
CBF-10
CBF-3
CBF-1,2,4
CBF-11
CNF-7,8
CAF-1 to 5, CAU-9,10
CNF-15,16
CBF-5
CNF-19
CAF-6 to 10
CNF-5,6
CNF-10,11
CAU-1 to 3, CNF-9
4.5.2.5 Phylogenetic relationships among pigeonpea Bradyrhizobium isolates in Adenta soil
as determined by combined matrices from RPO1 and RPO4 PCR.
All the 13 pigeonpea isolates (three from unfertilised treatments and ten from fertilised
treatments) from the Adenta soil together with the reference strain USDA110 were 66 % similar
(Fig. 20). Two main clusters, A and B, were formed beyond the mean similarity of 66 %. Cluster
A contained the reference strain USDA110 grouped together at 72 % similarity level with four
pigeonpea isolates from P fertilized treatments in the Adenta soil. In Cluster B, the three isolates
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from nodules of pigeonpea grown in the Adenta soil without P application were clustered
together at 71 % similarity with the remaining pigeonpea isolates from the Adenta soil with P
application. At 80 % similarity, nine sub-clusters were formed under clusters A and B. The
isolates in cluster A were differentiated into three sub-clusters (I, II and III). Isolate PAF-1 and
the reference strain were clustered separately into sub-clusters III and I, respectively. All the
three isolates within sub-cluster II were from nodules of pigeonpea grown in the Adenta soil
receiving P and were found to be 80 % similar. Cluster B consisted of six sub-clusters I, II, III,
IV, V and VI. Sub-cluster II contained isolates PAF-7 and PAF-9. Isolates PAF-10, PAF-6, PAF4 and PAF-3 were differentiated into separate clusters I, III, IV and V, respectively. The isolates
from nodules of pigeonpea that was grown in the P-unfertilised Adenta soil were clustered into
VI (Fig. 20). Isolates PAU-1 and PAU-2 were the most similar at 93 % level above which all the
isolates were dissimilar. The Shannon-Weaver diversity and the Pielou evenness indices were
1.95 and 0.94, respectively.
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PAU-2
II
VI
PAU-1
V
PAF-3
I
PAF-4
PAF-6
II
B
III
IV
V
PAU-3
II
PAF-7
I
PAF-10
III
PAF-9
PAF-1
PAF-5
II
A
II
PAF-2
I
PAF-8
0.66
0.73
0.80
Coefficient
USDA110
0.86
0.93
Fig. 20. Dendogram indicating relationships among Pigeonpea isolates in the Adenta soil
based on combined RPO1 and RPO4 PCRs
4.5.2.6 Phylogenetic relationships among pigeonpea Bradyrhizobium isolates in Bekwai soil
as determined by combined matrices from RPO1 and RPO4 PCR.
All the 20 isolates that nodulated pigeonpea in P-fertilised Bekwai soil were similar at 68 % level
(Fig. 21). The pigeonpea isolates were similar to the reference strain at 61 % similarity. Grouping
of all the isolates into Clusters A and B occurred beyond the mean similarity level of 61 %. All
the 20 isolates within cluster B were 68 % similar. At about 70 % similarity level, isolate PBF92
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20 was differentiated from the remaining isolates which were extensively differentiated beyond
73 % similarity level. At 80 % similarity, there was further differentiation within Cluster B
resulting in the formation of 11 sub-clusters (Fig. 21). Sub-cluster IV contained 25 % of the
isolates whereas 15 % of the isolates grouped under sub-cluster III. Isolates PBF-15 and PBF-18
were the most similar among the isolates at 89 % level. Beyond the 89 % similarity level, all the
isolates were dissimilar. Three pairs of isolates (PBF-11and PBF-12, PBF-1and PBF-5 and PBF4 and PBF-8) were similar at about 88 % level beyond which complete differentiated among all
the isolates occurred. The Shannon-Weaver diversity and the Pielou evenness indices were 2.20
and 0.92, respectively.
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XI
PBF-11
X
PBF-12
IX
PBF-16
VIII
PBF-17
PBF-14
VII
PBF-6
PBF-13
VI
PBF-19
PBF-15
PBF-18
PBF-7
V
PBF-1
IV
PBF-5
B
PBF-2
III
PBF-3
PBF-4
PBF-8
II
PBF-10
PBF-9
A
I
PBF-20
0.60
USDA110
0.67
0.75
Coefficient
0.82
0.89
Fig. 21. Dendogram indicating relationships among Pigeonpea isolates in the Bekwai soil
based on combined RPO1 and RPO4 PCRs
4.5.2.7 Phylogenetic relationships among pigeonpea Bradyrhizobium isolates in Nzima soil
as determined by combined matrices from RPO1 and RPO4 PCR.
All the 20 pigeonpea isolates (10 each from pigeonpea nodules from fertilised and unfertilised
Nzima soils) together with the reference strain USDA110 were 63 % similar (Fig. 22). Above
the mean similarity of 63 %, two main clusters, A and B were formed. Isolate PNF-7 was
clustered together with the reference strain USDA110 into A at a similarity of 68 %. The
remaining 19 isolates were clustered into B. All the isolates in cluster B were similar at 66 %
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level. At 80 % similarity, 12 sub-clusters were formed two of which were grouped under A with
the remaining ten sub-clusters grouped under B (Fig. 22). There was complete differentiation
between the reference strain and PNF-7 at 80 % similarity into separate clusters I and II,
respectively. Twenty five percent of the isolates were differentiated from the rest of the isolates
into separate clusters (Fig. 22). Within each of sub-cluster VIII and X an isolate from nodules of
P-fertilised pigeonpea plants was clustered together with two isolates from P-unfertilised plants.
Clusters IV and V contained isolates from nodules of P-fertilised pigeonpea plants. Isolates PNU3 and PNU-4 were the most similar at 91 % level beyond which all the isolates were dissimilar.
Isolates from the Nzima soil with P application were represented in five out of the six clusters
formed at 80 % similarity whereas isolates from the same soil without P application were
represented in only two out of the six clusters. The Shannon-Weaver diversity and the Pielou
evenness indices were 2.27 and 0.94, respectively.
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X
PNU-1
PNU-10
IX
PNF-3
PNU-5
VIII
PNU-3
PNU-4
VII
PNF-4
PNU-6
VI
PNU-7
PNU-8
V
PNU-9
PNF-6
IV
PNF-1
PNF-2
B
III
PNF-10
PNF-8
PNF-5
PNU-2
I II
I
A
II
PNF-9
0.62
0.69
0.77
Coefficient
PNF-7
USDA110
0.84
0.91
Fig. 22. Dendogram indicating relationships among pigeonpea isolates in the Nzima soil
based on combined RPO1 and RPO4 PCRs
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4.5.2.8 Phylogenetic relationships among pigeonpea Bradyrhizobium isolates from all the
soils as determined by combined matrices from RPO1 and RPO4 PCR.
From Fig. 23, the mean similarity of the 53 pigeonpea isolates from all the soils was 64 %. Above
the 64 % mean similarity level, the isolates were clustered into A and B. Isolate PNF-7 was
clustered together with the reference strain and isolate PAF-1 under A. Within cluster B, the
isolates were differentiated into three clusters, I< II and III at 70 % similarity level. Cluster B
was further clustered at 80 % similarity level into 28 sub-clusters with further clustering beyond
80 % similarity level. At the same 80 % similarity the two pigeonpea isolates in cluster A were
differentiated into two separate groups. The sub-clusters formed at 80 % similarity have been
summarised and presented in Table 5. From Table 5, it is evident that Cluster BI contained only
isolates from the Bekwai soil with P application. Within Cluster BIIa, isolate PNU-2 from the
unfertilized Nzima soil was grouped together with four isolates from the fertilized Adenta soil.
Cluster BIIb on the other hand, contained two isolates one each from the Nzima and the Adenta
soils with P. The groupings in III occurred at 74 % similarity and were further differentiated at
80 % similarity level. The cluster BIIIb contained only pigeonpea isolates from fertilized the
Nzima soil whereas BIIIc contained only isolates from fertilised Bekwai soil. Isolates from all
the soils with or without P were grouped under BIIIa and BIIIe. Within BIIId, isolate PNU-7
from unfertilised Nzima soil grouped together with isolate PBF-6 from fertilized Bekwai soil.
The isolates PAU-1 and PAU-2 were the most similar at 93 % similarity level. Beyond 93 %
similarity, all the isolates were dissimilar. The Shannon-Weaver diversity and the Pielou
evenness indices were 3.29 and 0.97, respectively.
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Table 5. Clustering isolates obtained from nodules on pigeonpea grown in the soils at 80 %
similarity
Similarity level
65 %
70 %
74 % 80 %
Cluster
Sub-cluster
Isolates
A
B
I
II
a
b
III
a
b
c
d
e
f
98
PNF-7
USDA110
PAF-1
PBF-9, 10
PBF-20
PAF-7, 9
PAF-6
PNU-2
PAF-4
PNF-5
PAF-3
PNU-5
PBF-11, 12
PAF-5,8
PNF-3, PBF-14, PNU-10, PAF-2
PNU-1, PAF-10
PNF-8,9
PNF-10
PBF-16
PBF-17
PNU-7, PBF-6
PNF-6
PNU-8,9
PNU-3,4, PNF-4
PBF-2
PBF-3,4,8
PBF-1,5,7
PBF-15,18,19
PNF-1,2
PNU-6, PBF-13
PAU-1,2,3,
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A
I
a
II
b
B
a
III
b
c
d
e
f
PAU-1
PAU-2
PAU-3
PBF-13
PNU-6
PNF-1
PNF-2
PBF-15
PBF-18
PBF-19
PBF-1
PBF-5
PBF-7
PBF-3
PBF-4
PBF-8
PBF-2
PNU-3
PNU-4
PNF-4
PNU-8
PNU-9
PNF-6
PBF-6
PNU-7
PBF-16
PBF-17
PNF-10
PNF-8
PNF-9
PAF-10
PNU-1
PAF-2
PNU-10
PBF-14
PNF-3
PAF-5
PAF-8
PBF-11
PBF-12
PNU-5
PAF-3
PNF-5
PAF-4
PNU-2
PAF-6
PAF-7
PAF-9
PBF-20
PBF-10
PBF-9
PAF-1
USDA110
PNF-7
0.64
0.71
0.78
0.86
0.93
Coefficient
Fig. 23. Dendogram indicating relationships among Pigeonpea isolates in the Adenta,
Bekwai and Nzima soils based on combined RPO1 and RPO4 PCRs
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4.5.2.9 Phylogenetic relationships among soybean Bradyrhizobium isolates in Adenta, and
Nzima soils as determined by combined matrices from RPO1 and RPO4 PCR.
The dendogram (Fig. 24) shows the level of similarity among 15 soybean isolates from Adenta
(13, all from fertilized treatments) and Nzima (2, all from fertilized treatments) soils and their
genetic relatedness to the reference strain USDA 110. All the soybean isolates were 62 % similar
to the reference strain. Beyond the mean similarity of 62 %, the isolates were grouped into two
main clusters, A and B. Isolate SAF-10 was the most similar to the reference strain, and was
grouped together with the reference strain in Cluster A at 66 % similarity level. The two isolates
from Nzima series were 64 % similar. All the isolates in cluster B were 73 % similar. At 80 %
similarity, the isolates were grouped into eight clusters all of which were dissimilar to the
reference strain, USDA 110. Isolates within Cluster B were differentiated into 7 sub-clusters (I,
II, III, IV, V, VI and VII) at the 80 % similarity level. Isolates SNF-2, SAF-12 and SAF-11 were
separately clustered into I, V, and VII, respectively. Isolates SAF-1 and SAF-13 with 80 %
similarity were clustered into VI. In sub-cluster IV, isolate SNF-1 from nodules of soybean
grown in the Nzima soil was grouped together with other isolates from the Adenta soil. The
isolates from the Nzima series were dissimilar at 80 % level and were genetically distant apart
(Fig. 24). Isolates SAF-6 and SAF-8 were the most similar at 98 % level. All the isolates were
dissimilar above 98 % similarity level. The Shannon-Weaver diversity and Pielou evenness
indices were 1.90 and 0.92, respectively for the clustering of all the soybean isolates. The
Shannon-Weaver diversity and Pielou evenness indices for isolates from only the Adenta and the
Nzima series were 1.58, 0.88 and 0.69, 1.00, respectively. In all, seven clusters were formed for
the soybean isolates from the Adenta Series.
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VII
.
SAF-11
VI
SAF-13
V
SAF-1
SAF-12
B
IV
SAF-2
SAF-3
SNF-1
III
SAF-4
SAF-5
SAF-6
SAF-8
II
SAF-7
I
II
SAF-10
USDA110
A
SNF-2
I
SAF-9
0.61
0.70
0.79
Coefficient
0.89
0.98
Fig. 24. Dendogram indicating relationships among soybean isolates in Adenta and Nzima
soils based on combined RPO1 and RPO4 PCRs
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4.5.2.10 Phylogenetic relationships among Bradyrhizobium isolates from soybean,
pigeonpea and cowpea grown in Adenta soil as determined by combined matrices from
RPO1 and RPO4 PCR.
The mean similarity for the 57 isolates from Adenta series was 64 % (Fig. 25). Above the mean
similarity level, the isolates were grouped into two main clusters A and B. The isolates in A were
75 % similar whereas the isolates in B were 67 % similar. At 80 % similarity, eighteen subclusters were formed among the isolates obtained from the Adenta soil. The three isolates in
cluster A were those that nodulated soybean in P-fertilised treatments. About 95 % of the isolates
were grouped in cluster B and were differentiated into 16 sub-clusters (Fig 25 and Table 6).
Cluster BI contained three isolates from soybean, pigeonpea and cowpea grouped together with
the reference strain USDA 110. Within BIIa, one soybean isolate SAF-11 was clustered together
with one pigeonpea isolate PAF-10 all from fertilised treatments. The clusters BIIb, BIId and
BIIe contained four, one and four pigeonpea isolates, respectively from fertilised treatments. The
eight soybean isolates within cluster BIIc were those obtained from fertilised treatments. Within
BIIf, two unfertilised pigeonpea isolates were clustered together with cowpea isolates from either
P-fertilised or P-unfertilised treatments. At 80% similarity, none of the isolates were similar to
the reference strain. Isolates SAF-6 and SAF-8 were the most similar with 98 % similarity.
Beyond 98 % similarity level, all the isolates were dissimilar. The sub-clusters formed at 80 %
similarity are presented in Table 6 for simplicity. The Shannon-Weaver diversity and the Pielou
evenness indices were 2.51 and 0.86, respectively.
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Table 6. Clustering isolates obtained from nodules on legumes grown in Adenta soil at 80
% similarity
Similarity level
65 %
67 %
74 % 80 %
Cluster
Sub-cluster
Isolates
A
B
I
II
a
b
c
d
e
f
f
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SAF-13, SAF-1
SAF-12
USDA 110
SAF-10
PAU-3, CAU-11
SAF-11
PAF-10
PAF-5,8
PAF-2
PAF-1
SAF-6,7,8,9
SAF-2,3,4,5
PAF-3
PAF-7,9
PAF-6
PAF-4
CAF-1,2,3,4,5, CAU-9,10
CAF-6,7,8,9,10, PAU-1,2, CAU-5
CAU-1,2,3,4, 6,78
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A
I
a
b
B
c
II
d
e
f
CAU-1
CAU-2
CAU-3
CAU-4
CAU-8
CAU-6
CAU-7
CAU-5
PAU-1
PAU-2
CAF-10
CAF-6
CAF-7
CAF-8
CAF-9
CAU-10
CAF-3
CAU-9
CAF-1
CAF-4
CAF-2
CAF-5
PAF-4
PAF-6
PAF-7
PAF-9
PAF-3
SAF-2
SAF-3
SAF-4
SAF-5
SAF-6
SAF-8
SAF-7
SAF-9
PAF-1
PAF-2
PAF-5
PAF-8
PAF-10
SAF-11
CAU-11
PAU-3
SAF-10
USDA110
SAF-12
SAF-13
SAF-1
0.63
0.72
0.80
Coefficient
0.89
0.98
Fig. 25. Dendogram indicating relationships among isolates from Adenta soil based on
combined RPO1 and RPO4 PCRs
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4.5.2.11 Phylogenetic relationships among Bradyrhizobium isolates from Bekwai soil as
determined by combined matrices from RPO1 and RPO4 PCR.
The mean similarity of the 32 isolates from Bekwai series was 61 % (Fig. 26). Two main clusters
A and B were formed above the mean similarity level of 61 %. The reference strain was separated
into cluster A. Cluster B consisted of cowpea and pigeonpea isolates from the Bekwai series with
a mean similarity of 66 %. At 80 % similarity, 16 sub-clusters were formed under cluster B.
Cluster BI contained only isolates from pigeonpea grown in fertilised soils. Cluster BIIa also
contained only isolates from pigeonpea whereas two isolates from fertilised pigeonpea and
fertilised cowpea were grouped in BIIb. Within BIId, isolate CBF-3 and from fertilised cowpea
was clustered grouped together with 11 isolates from fertilised pigeon pea. Clusters BIIe, BIIf
and BIIg contained isolates from cowpea in fertilised soils. At the highest similarity of 93 %, the
isolates CBF-7 and CBF-8 were similar. All the isolates were dissimilar beyond 93 % similarity.
The sub-clusters formed at 80 % similarity are presented in Table 7 for simplicity. The ShannonWeaver diversity and the Pielou evenness indices were 2.62 and 0.97, respectively.
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Table 7. Clustering isolates obtained from nodules on legumes grown in Bekwai soil at 80
% similarity
Similarity level
62 %
68 %
Cluster
Sub-cluster
A
B
75 % 80 %
Isolates
I
II
a
b
c
d
e
f
g
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USDA 110
PBF-9,10,
PBF-20
PBF-16
PBF-11,12,
PBF-17, CBF-6
PBF-6,14
PBF-3,4,8
PBF-2
PBF-7,13,15,18,19
PBF-1,5, CBF-3
CBF-12
CBF-7-10
CBF-5
CBF-1,2,4,
CBF-11
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a
a
A
I
a
a
b
c
B
d
II
e
f
g
CBF-11
CBF-1
CBF-4
CBF-2
CBF-5
CBF-10
CBF-7
CBF-8
CBF-9
CBF-12
CBF-3
PBF-1
PBF-5
PBF-13
PBF-19
PBF-15
PBF-18
PBF-7
PBF-2
PBF-3
PBF-4
PBF-8
PBF-14
PBF-6
CBF-6
PBF-17
PBF-11
PBF-12
PBF-16
PBF-20
PBF-10
PBF-9
USDA110
0.60
0.68
0.77
Coefficient
0.85
0.93
Fig. 26. Dendogram indicating relationships among isolates from Bekwai series based on
combined RPO1 and RPO4 PCRs
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4.5.2.12 Phylogenetic relationships among Bradyrhizobium isolates from Nzima series as
determined by combined matrices from RPO1 and RPO4 PCR.
Figure 27 showed that all the 41 isolates in the Nzima soil were 62 % similar. The isolates from
Nzima series were differentiated into clusters A and B beyond the mean similarity of 62 %.
Isolate PNF-7 was clustered together with the reference strain USDA110 in cluster A at 68 %
similarity. The isolates within cluster B were grouped into twenty new clusters (Fig. 27) at 65 %
similarity level. At 71 % similarity level, the isolates within cluster BII were further differentiated
into sub-clusters a, b, c, d and e. At 80 % similarity, the isolates from Nzima series were
differentiated into 21 clusters. Isolate PNU-2 and PNF-1 were the only isolates in Clusters BI
and BIIb, respectively. Cluster BIIa consisted of the isolates from soybean clustered together
with some cowpea isolates. Three isolates from fertilised pigeonpea and two isolates from
fertilised cowpea were grouped under BIIc. Within BIId cowpea isolates CNF-7 and CNF-8 were
grouped together with pigeonpea isolates from either fertilised or unfertilised treatments. Four
fertilised cowpea isolates formed one group BIIe together with two isolates from unfertilised
pigeonpea and five isolates from fertilised soils. The isolates CNF-15 and CNF-16 were the most
similar at 98 % similarity. The isolates were completely differentiated into clusters containing
single isolates beyond 98 % similarity. For simplicity, the main clusters formed at 80 % similarity
and their sub-clusters at higher similarity levels are presented in Table 8. The Shannon-Weaver
diversity and the Pielou evenness indices were 2.81 and 0.92, respectively.
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Table 8. Clustering of isolates obtained from nodules on legumes grown in Nzima soil at 80
% similarity
Similarity level
63 %
65 % 71 % 80 %
Cluster
Sub-cluster
A
B
I
II
a
b
c
d
e
109
Isolates
USDA 110
PNF-7
PNU-2
SNF-1
CNF-12-14
SNIF-2, CNF-1,2,17,18
PNF-5
PNF-8,9,10
CNF-3
CNF-19
PNF-1,2
PNF-6
PNU-6
PNF-4, PNU-3,4
PNU-7,8
CNF-7,8
PNU-5
CNF-5,6
CNF-10,11
CNF-15,16
PNU-1, PNF-3
CNF-4,9, PNU-10
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A
I
a
B
b
II
c
d
e
CNF-9
PNU-10
CNF-4
PNU-1
PNF-3
CNF-15
CNF-16
CNF-10
CNF-11
CNF-5
CNF-6
PNU-5
CNF-7
CNF-8
PNU-7
PNU-8
PNU-9
PNU-3
PNU-4
PNF-4
PNU-6
PNF-6
PNF-1
PNF-2
CNF-19
CNF-3
PNF-10
PNF-8
PNF-9
PNF-5
CNF-18
CNF-17
CNF-1
CNF-2
SNF-2
CNF-12
CNF-13
CNF-14
SNF-1
PNU-2
PNF-7
USDA110
0.61
0.70
0.79
Coefficient
0.89
0.98
Fig. 27. Dendogram indicating relationships among isolates from Nzima series based on
combined RPO1 and RPO4 PCRs
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CHAPTER FIVE
5.0 DISCUSSION
5.1 Physico-chemical properties of the Adenta, Bekwai and Nzima series.
The particle size distribution and the dry bulk density for the soil from the coastal savannah
Haplic Acrisol agrees with the findings of Dowuonna et al. (2012) who classified the coastal
savannah Haplic Acrisol as sandy clay loam. The particle size distribution and the dry bulk
densities reported for the Ferric Acrisol and the semi-deciduous Haplic Acrisol from this study
are the same as reported by Adu (1992) and Owusu-Bennoah et al. (2000) who classified these
soils from the semi-deciduous forest as clay soils. The bulk densities for all the soils (1.35-1.49
Mg/m3) were medium and as such should not be growth limiting, using the growth limiting bulk
density (GLBD) values for the different textural classes of soils (Appendix 1) reported by
Daddow and Warrington (1983). However, based on the GLBD value of 1.4 Mg/m3 (Morris and
Lowery, 1988; Coder, 1995; Coder, 1996), the bulk densities of these clay textured soils from
the semi-deciduous forest could have the potential to limit plant growth. The effect of GLBD on
plant growth has been reported by Jaramillo-C et al. (1992) who stated that soils with dry bulk
densities found to be growth limiting (compacted soils), often limit the root length of crops
growing in those soils thus preventing plants from exploring nutrients within the larger soil
volume for growth.
The Adenta soil from the coastal savannah agro-ecological zone had higher available P than the
soils from the semi-deciduous agro-ecological zone. The low levels of available P in the soils
from the semi-deciduous forest may be due to low levels of mineral apatite in the parent material
(Acquaye and Oteng, 1972; Adu, 1992) and or may also be due to P-fixation in low pH soils
through reactions with Fe and Al hydroxides (Sanchez and Salinas, 1981; Mokwunye et al., 1986;
Warren, 1992; Juo and Fox, 1997; Abekoe and Sahrawat, 2001).
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The Bekwai and Nzima soils have high organic carbon content and total nitrogen partly due to
the high litter deposition from the canopies as well as low organic matter turnover in the semideciduous soils. Similar findings have been reported by Jones et al. (2006).
The higher CEC values for Bekwai and Nzima may be due to the high proportions of clay in
these soils and the presence of considerably high organic carbon compared to the Adenta soil.
Similar findings have been reported by Dwomo and Dzedzoe (2010).
5.2 Populations of indigenous Bradyrhizobia nodulating soybean and cowpea in the
Adenta, Bekwai and Nzima series.
The presence of cowpea and soybean nodulating Bradyrhizobium spp. in the three Ghanaian soils
examined suggests that these soils do provide favourable conditions for the Bradyrhizobium spp.
to live saprophytically in the absence of their symbiotic host legumes. Similar findings have been
reported by Duodu et al, (2005).
The wide range of Bradyrhizobium spp. that nodulated cowpea and soybean in the studied soils
further suggests that growth conditions were more favourable in some soils and that some of the
soils may have an unknown history of legume cultivation. This finding agrees with that of
Abaidoo et al. (2007). The population of Bradyrhizobium cells that nodulated soybean were low
in all the soils compared to the population of Bradyrhizobium spp. nodulated cowpea suggesting
that soybean is more specific compared to cowpea in rhizobia strain selection and that cowpea
as a promiscuous legume is nodulated by a larger pool of Bradyrhizobia. This may be due to the
fact that legumes within the cowpea cross-inoculation group nodulate only with subgroups of the
indigenous populations of Bradyrhizobium spp. (Burton, 1979; Thies et al., 1991; Abaidoo et al.,
2007; Jaramillo et al., 2013).
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5.3 Effect of P application on nodulation of soybean and pigeonpea grown in the Adenta
and Bekwai series.
In both the Adenta and the Bekwai soils, the addition of soluble P fertilizer generally had highly
positive effects on nodulation and nodule growth. Phosphorus is known to be the main energy
source for powering nodulation of legumes (Gentili and Huss-Danell, 2003). Nodule P
requirements forms a greater portion of a legume's total P requirement (Bonetti et al., 1984; Qin
et al., 2012). Hence, the increased nodulation with P addition which is similar to earlier reports
(Singh et al., 1981; Rao and Reddy, 1997; Olivera et al., 2004), is expected.
While these responses applied to both legumes used in this study, the magnitude was often
influenced by the soil type and legume genotype. For example, while in the Adenta soil,
pigeonpea gave higher responses than soybean with P application up to 120 kg P/ha, the
application of P above 120 kg P/ha decreased the number of nodules formed on pigeonpea but
not on soybean. Plant species differ in their relation with mycorrhizal fungi as well as the
response of arbuscular mycorrhizal association to varying levels of P in soil solution (Kahiluoto
et al., 2000). Thus, plants with extensive fibrous roots are often less dependent on mycorrhizae
compared to plants having less extensive root systems (Plenchette et al., 1983). Pigeonpea is
known to release bond sources of P in soil by its root exudates (Ae et al., 1990) and mycorrhizal
association (Dighton et al., 1993). This together with the high phosphorus utilisation efficiency
of pigeonpea which makes the legume adapt to soils with low P status (Ascencio and Lazo, 2001)
may have contributed to the higher response of pigeonpea to P application than soybean in this
study. Similar findings on differences in legumes’ P requirements for nodulation and nitrogen
fixation in different soils have been reported (Shu jie et al., 2007). Phosphorus application that
usually exceeds that required by plants have been reported to result in decreased mycorrhizal
development (Chulan and Ragu, 1986). When the release of P from fertilizers is not in balance
with the plant demand, it results in increased P concentration in the soil’s solution near the
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rhizosphere. The excess P in solution is bound to Ca, Mg or to Fe and Al oxides through fixation
reactions (Mitchell, 1957; Sample et al., 1980). The nutrients Ca, Mg and Fe therefore become
unavailable to the growing plant. At this stage growth ceases and further developments are
retarded and may be the reasons why higher rate of P application decreased nodulation in
pigeonpea. Shekhar and Sharma (1991) reported similar decreases in nodulation parameters in
Pisum sativum when phosphorus was applied above a threshold rate.
5.4 Effect of N application on nodulation of soybean and pigeonpea grown in the Adenta
and Bekwai series.
Application of nitrogen generally decreased the number of nodules and also the dry weight of
nodules formed. The N2 fixation process together with the assimilation of the end product is high
and costly in terms of energy (Evans et al., 1980; Al-Neimi et al., 1997) compared to the energy
cost of assimilating supplied N (Salsac et al., 1987; Bloom et al., 1992). As such, leguminous
plants will prefer mineral N to fixed N2 when presented with these two options. Such conditions
do not favour the nodulation of the growing legume and the process is inhibited (Danso et al.,
1990; Abdel-Wahab et al., 1996). Higher levels of mineral N in soils have been reported to
depress nodulation (Davidson and Robson, 1986; Eaglesham, 1989; Gentilli and Huss-Dannel,
2002) and nitrogen fixation in actively growing legumes (Herdina and Silsbury, 1989; Sun et al.,
2008).
That nodules were formed and their weights could not be measured by the scale used suggests
that nodule growth may have been more severely affected than nodule initiation. In the presence
of high soil mineral N, there is reduced supply of carbohydrates to nodules for nitrogenase
activity (Streeter, 1985). Nitrogenase activity is therefore inhibited by this process (Purcell and
Sinclair, 1990; Sanginga et al., 1996; Arreseigor et al., 1997). This together with decreased
diffusion of oxygen into nodules causes restricted respiration of bacteriods (Gordon et al., 2002)
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which may have inhibited the development of the nodules formed (Atkins et al., 1984; Imsande,
1986; Sodek and Silva, 1996) and consequently decreased the weight of nodules formed at higher
N rates.
5.5 The counteracting effect of P on nodulation inhibition by soil inorganic N by soybean
and pigeonpea grown in the Adenta and Bekwai series.
Where high soil mineral N had completely “knocked-off” nodulation and nodule growth,
application of phosphorus revived nodulation and nodule growth in all cases. However, the levels
of phosphorus required differed for the different soils and for the different legumes. Due to its
key role in the energy metabolism of all plant cells and particularly in nitrogen fixation (Dilworth,
1974), P application has been reported to increase nitrogenase activity, photosynthetic rate and
legume biomass production (Geneva et al., 2006). With increased photosynthetic rate and
biomass production the plant grows bigger with a higher N requirement. The increased N
requirement for growth leads to increased N uptake from the soil thereby reducing the N in the
soil (Corti et al., 2005) to a low level where N inhibition is “knocked-off”. This finding is
supported by earlier reports that where nodule numbers and nodule dry weights were inhibited
by N application, there was a counteracting effect by high P (Gentili and Huss-Danell, 2002).
Soybean grown in the Bekwai soil was not noduated at all. The inability of soybean to nodulate
in the Bekwai soil may be due to factors other than P. Similar findings on the inability of soybean
to nodulate in the Bekwai soil have been reported by Klogo (2006).
5.6 Effect of N and P application on shoot dry weight of soybean and pigeonpea grown in
the Adenta and Bekwai series.
Application of P increased the dry weight of shoots produced by the legumes in both soils.
However, in the Adenta soil, P application above 160 kg/ha decreased pigeonpea shoot
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production. The importance of P in promoting vegetative growth and nodulation as well as N2
fixation as stated earlier (Dilworth, 1974; Gentili and Huss-Danell, 2002; Geneva et al., 2006)
may have been the reasons for the increased shoot biomass observed. Similar findings on P
application on increased biomass production have been reported (Gate and Wilson, 1974;
Olofintoye, 1986; Pereira and Bliss, 1987). Also, the decreased dry weight of pigeonpea shoots
observed with high P application could be due to the problems as associated high P in soils stated
earlier (Mitchell, 1957; Sample et al., 1980; Chulan and Ragu, 1986; Shekhar and Sharma, 1991).
This observation is similar to the findings of Tsvetkova et al., (2003).
The study again showed that nitrogen application increased shoot production by the legumes in
both soils. In the Bekwai soil series, increased dry weight of pigeonpea shoots were observed at
all rates of N applied. The increase in the dry weight of shoots with nitrogen application gives an
indication of the N requirements of these legumes for adequate growth and development (Walker
et al., 2001) and that the soils’ solution do not contain enough N to satisfy all the N requirements
of legumes, neither was N2 fixation high enough to provide all the additional N required. This
finding is in agreement with work done by Singleton et al. (1985) who reported that N application
enhances shoot dry weight production.
In the Adenta series, however, N application above 80 kg N/ha decreased dry shoot production
by both legumes. This may be due to toxicity induced by oversupply of N. Similar findings of
decreased shoot production due to N toxicity have been reported for soybean varieties grown in
some Ghanaian soils (Fening, 1999).
The combined application of N and P in this study enhanced shoot dry weight production by both
legumes. Because of its importance in energy metabolism (Dilworth, 1974) and the ability to
increase nitrogenase activity, photosynthetic rate and legume biomass production (Jia et al.,
2004: Geneva et al., 2006), P application results in increased plant N uptake from soils thereby
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reducing the N in the soil (Corti et al., 2005). In this way, any toxicity effect induced by the high
N in the soil (Fening, 1999) is also reduced.
A similar finding was reported by Gentilli and Huss-Danell (2002) who concluded that in low P
soils the dry weight of shoots produced is low compared to the high dry weight of shoots (10fold increase) at high P levels under toxic levels of N.
Although P effect was general on growth of the legumes, its effect was more drastic on
nodulation. This may be due to the more P requirement for nodule initiation and development
which often sinks more of the supplied P (Eaglesham and Ayanaba, 1984), the excess of which
is used for enhancing vegetative growth (Jia et al., 2004; Geneva et al., 2006). Similar finding
has been reported by Wall et al. (2000).
5.7 Effect of phosphorus application on nitrogen fixation by soybean in Adenta series.
Phosphorus application though increased the nodulation of soybean by the indigenous
Bradyrhizobium populations, the tendency with increased P was for the dry weight per nodule
formed and perhaps nodule size too to be the same as that of the control. Phosphorus application
had no significant positive effect on the dry weights per nodule formed in this study. Without P
application, the indigenous populations of Bradyrhizobium that nodulated soybean fixed only
15.57 mg N/ pot equivalent to 15.57 kg N/ ha in the soil. The total N derived from atmospheric
N2 fixed constituted 23.1 % of the total N in shoot. With P application, nodulation in the soybeanBradyrhizobium symbiosis was enhanced, resulting in increased total N accumulation in the
shoot up to the 120 kg P/ha rate where 51.50 mg N/ pot equivalent to 51.50 kg N/ ha was derived
from fixation. This finding could be explained by the conclusions that phosphorus enhances
photosynthetic rate and biomass production (Jia et al., 2004) as well as nitrogenase and acid
phosphatase activities (Geneva et al., 2006; Olivera et al., 2004). Eventually the plant grows
bigger with a higher N demand which leads to an increased N uptake from soil. With increased
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N uptake, the soil's N is depleted and mechanisms for nodulation and nitrogen fixation is initiated
especially in soils with low N status. This finding is in line with results reported earlier for
increased nodulation and also increased amount of nitrogen fixed with P addition (Herridge et
al., 2008; Salvaglotti et al., 2008). In uninoculated soils, N2 fixation induced by an indigenous
bradyrhizobial community supplies less than optimal amounts of nitrogen (Sanginga et al., 2002).
Most of the increase in N2 fixation with P addition was in total N2 fixed rather than in % Ndfa,
with the greatest increase in % Ndfa occurring with the first addition of P, from 0 kg P/ ha to 40
kg P/ ha. This observation is similar to the trend reported by Sanginga et al. (1990).
5.8 Diversity of indigenous Bradyrhizobium strains nodulating soybean, pigeonpea and
cowpea in Adenta and Bekwai series as determined by combined RPO1 and RPO4 PCRs.
The results from the present study have shown that the indigenous bradyrhizobial isolates that
nodulated cowpea, soybean and pigeonpea grown in the soils studied differed genetically and
were highly diverse. Polymerase chain reactions (PCR) using RPO1 and RPO4 primers were able
to generate a high degree of polymorphic Bradyrhizobium DNA (Versalovic et al., 1994;
Teaumroong and Boonkerd, 1998; El-Fiki, 2006). The resulting multiple DNA fragments had
band sizes ranging between 117-1800 bp and 157-3000 bp for the RPO1 and RPO4 PCR
respectively. These band sizes corresponded to the expected sizes reported previously
(Richardson et al., 1995; Sikora and Redzepovic, 2003). The 1500 bp and 2900 bp DNA
fragments for the 16S and 23S gene PCR were also expected (Pronk and Sanderson, 2001;
Yasuda and Shiaris, 2005; Zhu et al., 2007). The use of combined matrices of RPO1-PCR and
RPO4-PCR in the present study to discriminate among bradyrhizobial isolates was successful
and the observation made agrees with earlier reports (Bostock et al., 1993; Wang et al., 1993;
Sikora et al., 1997; Wolde-meskel et al., 2005; El-Fiki, 2006).
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The high diversity in indigenous populations of Bradyrhizobia that nodulated legumes in this
study is similar to work done elsewhere on rhizobia (Madrzak, et al., 1995; Niemann et al., 1997;
Ando, et al., 1999).
Several researchers have reported on the effect of environmental variables and management
practices on population structure and diversity under field conditions where host legumes were
previously absent (Bala et al., 2001; Andrade et al., 2002; Depret et al., 2004; Kaschuk et al.,
2006). The diversity of rhizobia between sites (Mothapo et al., 2013) is usually due to prevailing
site-specific environmental variables imposing general genetic adaptations on soil rhizobia
(Bernal and Graham, 2001; Mutch et al., 2003; Tian et al., 2007; Yang et al., 2006; Farooq and
Vessey, 2009). Compared to the semi-deciduous forest soils, the Adenta soil from the coastal
savannah agro-ecological zone supported a low diversity of bradyrhizobia that were capable of
nodulating pigeonpea and cowpea. Conversely, the diversity of Bradyrhizobium from the Adenta
soil that nodulated soybean was higher than that for the soybean isolates from the Nzima soil.
Earlier reports show that soils from humid regions have relatively high diversities of nitrogenfixing bacteria than those from semi-arid regions (Wasike et al., 2009). Similar findings have
also been reported by Danso and Owiredu (1988) and Rupela et al. (1982). The high diversity of
the pigeonpea isolates from this study may be due to the low specificity of the legume in terms
of nodulating with indigenous rhizobial communities as previously reported (Coutinho et al.,
1999; Lombardi et al., 2009).
5.9 Effect of Phosphorus on the diversity of indigenous Bradyrhizobium strains nodulating
soybean, pigeonpea and cowpea in Adenta, Bekwai and Nzima series.
Application of P in the Adenta soil decreased the diversity of Bradyrhizobium that nodulated
cowpea. Different levels of phosphorus are stored by different strains of Bradyrhizobium
japonicum (Cassman et al., 1981). The nitrogen fixing capability of superior strain-legume
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symbiosis is usually at the highest level of P application (Erman et al., 2009). These conclusions
together with the selectivity for effective strains (Perret et al., 2000) under N-limited conditions
may have led to the selection of strains which were similar in this case and dominated the
nodulation of this legume or that some of the different strains that nodulated the cowpea prior to
P addition were suppressed in the presence of added P.
Contrary to the observation made for cowpea in the Adenta soil, the diversity of the isolates that
nodulated pigeonpea in both the Adenta and Nzima soils was increased with P addition. The
same explanation given for enhanced nodulation of some cowpea isolates from the Adenta soil
with P application may be applicable to this observation except that the higher diversity observed
with P application may be that pigeonpea in addition, was nodulated by the strains that nodulated
when no P was applied or that the enhanced strains in this case were diverse.
It is suspected that Bradyrhizobium japonicum strains may be present in the Adenta and Nzima
soils but absent in the Bekwai soil. Results on soybean not being nodulated by indigenous
Bradyrhizobial populations in Bekwai soil have been reported by Attuah (2001). However, upon
inoculation with Bradyrhizobium japonicum strain USDA 110 it was found that the legume was
profusely nodulated (Attuah, 2001). These findings are in agreement with reports that where a
high degree of host-specificity exists between legume hosts and rhizobial species (Thrall et al.,
2000) loss of a single rhizobial species can result in loss of nodulation and N2-fixation by that
legume (Lowendorf et al., 1980).
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CHAPTER SIX
6.0 SUMMARY CONCLUSION AND RECOMMENDATIONS
The present study aimed at studying the nodulation and nitrogen fixation of soybean and
pigeonpea under phosphorus fertilization and the need for Bradyrhizobium inoculation in
Ghanaian soils.
The presence of bradyrhizobia indigenous to Ghanaian soils that are capable of nodulating with
soybean and cowpea has been reported. The populations of bradyrhizobia nodulating soybean
and cowpea in Ghanaian soils estimated by the MPN plant infection assay vary widely ranging
from 0.7×101 cells/ g soil to 7.8×103 cells/ g soil. The soils from the semi-deciduous forests were
found to harbour more indigenous cowpea bradyrhizobial populations than the soil from the
coastal savannah. The Ferric Acrisol contained the highest population (7.8×103 cells/ g soil) of
cowpea nodulating Bradyrhizobium, however, the least population of Soybean nodulating
Bradyrhizobium (0.7×101 cells/ g soil) was observed in this soil. The semi-deciduous Haplic
Acrisol contained the highest population of soybean rhizobia (4.5×102 cells/ g soil). Soybean is
probably nodulated by both bradyrhizobia belonging to the cowpea miscellany and those that do
not belong to the cowpea miscellany.
Application of P generally increased nodulation and growth of nodules except for soybean grown
in the Ferric Acrisol. Nitrogen application inhibited nodulation in the legumes up to levels where
complete inhibition of nodulation and growth of nodules occurred. Application of P in
combination with an inhibitory rate of N revived nodulation and nodule growth in all cases.
Single applications of N and P generally increased shoot dry weight production except in some
few cases where higher applications resulted in decreased shoot production. Combined
application of N and P also increased shoot dry weight production by the legumes. However, at
higher rates of combined N and P, toxicity was induced on shoot dry weight production.
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The present study investigated the nitrogen fixing potential of the indigenous bradyrhizobia on
soybean in the Coastal savannah Haplic Acrisol. Without P application, the soybeanBradyrhizobium symbiosis fixed 15.57 kg N/ ha equivalent to 23.1 % of the total N in shoot.
Phosphorus application increased the amount of nitrogen fixed by the symbiosis, and by the 120
kg P/ ha rate, the amount fixed was more than 3 times that of the control without P, and was
equivalent to 54.7 % of the total N in shoot. Thus, with 120 kg P/ ha applied, the indigenous
populations of bradyrhizobia through symbiosis were able to supply the soybean cultivar Anidaso
with more than half of its total nitrogen requirement.
The combined DAPD and RAPD fingerprinting patterns have been able to successfully
discriminate within and between isolates that nodulated cowpea, pigeonpea and soybean in the
soils under study. The cluster analysis revealed that a high diversity existed within and between
indigenous bradyrhizobial isolates that nodulated cowpea, pigeonpea and soybean grown in the
soils from different agro-ecological zones in Ghana. The diversity of isolates from the different
phosphorus fertilized soils that nodulated soybean, pigeonpea and cowpea varied considerably.
For example, whereas P application reduced the diversity of cowpea isolates from the coastal
savannah Haplic Acrisol, the diversity of pigeonpea isolates from the same soil were increased
with P application.
The diversities identified especially for soybean considering the nitrogen fixing potentials of the
symbiosis represents a valuable genetic resource potential for selecting more competitive and
effective strains for inoculum production to improve BNF and increase the yields of the legumes
at a low cost of production.
I would recommend that

To achieve maximum benefits from the symbiosis, P fertilization is essential, especially
for our soils that are generally low in available P
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
Nitrogen fertilization generally is inhibitory to N2 fixation, and is not recommended if the
maximum benefits from BNF are expected.

In soils where nodulation and N2 fixation are inhibited by nitrogen availability, the
application of P fertilizer is essential to counter the inhibitory effects of the high soil N
on nodulation and N2 fixation.

The high diversity of bradyrhizobia observed although could ensure the nodulation of
different tropical legumes by the indigenous strains without the need for artificial
inoculation, there is the possibility that these legumes could be nodulating with the
diverse array of these bradyrhizobia, of which a proportion might not be active in fixing
N2 on that particular legume because they are not specific to it. For this reason, more
studies are necessary to assess actual N2 fixed with or without inoculation by selected,
highly effective strains, distinct from number of nodules formed, so as to assess the need
for inoculation of many of these legumes..

Based on the higher yield of the N-fertilized legumes than the unfertilized controls, it
appears that the indigenous bradyrhizobia were not highly efficient and could therefore
not fix the optimum amounts of N required for the growth of these legumes. Such results
call for the use of rhizobial inoculation with strains more effective than the indigenous
ones.
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APPENDICES
Appendix 1
USDA soil texture triangle
Source: Soilsensor.com (http://www.soilsensor.com/soiltypes.aspx)
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Appendix 2
Growth- Limiting bulk density textural triangle
Source: Warrington and Dadow (1983)
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Appendix 3
Effect of Phosphorus application on the diversity of Bradyrhizobium nodulating soybean,
pigeonpea and cowpea growing in Adenta, Bekwai and Nzima series.
Indices
Legume NI
Cowpea
Soil
Diversity
Evenness
Effect of P on diversity
New strains
21
Adenta
1.22
0.88
-
Yes
12
Bekwai
1.74
0.90
NA
NA
19
Nzima
2.11
0.91
NA
NA
52
All
2.75
0.90
Pigeonpea 13
Adenta
1.95
0.94
+
Yes
20
Bekwai
2.20
0.92
NA
NA
20
Nzima
2.27
0.94
+
Yes
53
All
3.29
0.97
13
Adenta
1.58
0.88
NA
NA
2
Nzima
0.69
1.00
NA
NA
15
All
1.90
0.92
47
Adenta
2.51
0.86
32
Bekwai
2.62
0.97
41
Nzima
2.81
0.92
Soybean
All
NB:
- = P application increased diversity
+ = P application decreased diversity
0 = P application had no effect on diversity.
NI= Number of isolates
NA = Not applicable Indicating that there were no nodules formed without P
application
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